Introduction

For one of my machine learning classes we had a project that consumed financial data. I have extended that project to use machine learning to see if an indicator, or predictor, can be found that identifies market tops that occur prior to recessions. Then I use the model to build a trading strategy and backtest it to see how it performs.

Get Economic and Financial Data

Acquiring the data consists of two steps. First the code pulls the data into zoo objects which are then collapsed into a single data frame (df.data). Features are extracted from these series and added to the df.data data frame.

Sample call to pull economic data

Data is pulled from several sources include FRED, yahoo, and Google. The code below shows an example that pulls in the consumer price index (CPI) from the FRED. I pull data using quantmod, Quandl, and some manual extractions stored in spreadsheets.

# Consumer Price Index for All Urban Consumers: All Items
if (bRefresh == TRUE) {
  getSymbols("CPIAUCSL", src = "FRED", auto.assign = TRUE)
}
## [1] "CPIAUCSL"
## Warning: ASDAX contains missing values. Some functions will not work if objects
## contain missing values in the middle of the series. Consider using na.omit(),
## na.approx(), na.fill(), etc to remove or replace them.
## Warning: ^TNX contains missing values. Some functions will not work if objects
## contain missing values in the middle of the series. Consider using na.omit(),
## na.approx(), na.fill(), etc to remove or replace them.
## Warning: CL=F contains missing values. Some functions will not work if objects
## contain missing values in the middle of the series. Consider using na.omit(),
## na.approx(), na.fill(), etc to remove or replace them.
## Warning: ^IRX contains missing values. Some functions will not work if objects
## contain missing values in the middle of the series. Consider using na.omit(),
## na.approx(), na.fill(), etc to remove or replace them.
## Warning: ^RLG contains missing values. Some functions will not work if objects
## contain missing values in the middle of the series. Consider using na.omit(),
## na.approx(), na.fill(), etc to remove or replace them.
## Warning: ^STOXX50E contains missing values. Some functions will not work if
## objects contain missing values in the middle of the series. Consider using
## na.omit(), na.approx(), na.fill(), etc to remove or replace them.
## Warning: TMFGX contains missing values. Some functions will not work if objects
## contain missing values in the middle of the series. Consider using na.omit(),
## na.approx(), na.fill(), etc to remove or replace them.

Load up the EIA data

Load rig count data

The Baker Hughes rig count numbers

USDA data

Loading in farm data

## Warning in read_fun(path = enc2native(normalizePath(path)), sheet_i = sheet, :
## Expecting numeric in E3 / R3C5: got a date
## New names:
## * `` -> ...1
## * `` -> ...2
## * `` -> ...3
## * `` -> ...4
## * `` -> ...5
## * ...
## Warning: NAs introduced by coercion

Loading in Silverblatt’s S&P 500 spreadsheet starting with the quarterly data.

## New names:
## * `` -> ...2
## * `` -> ...3
## * `` -> ...5
## * `` -> ...6
## * `` -> ...7

Now load in the estimates

## New names:
## * `` -> ...2
## * `` -> ...3
## * `` -> ...4
## * `` -> ...5
## * `` -> ...6
## * ...

Covid 19 Data

Get the Covid-19 data from JHU

## Rows: 663741 Columns: 15
## -- Column specification ------------------------------------------------------------------------------------------------
## Delimiter: ","
## chr  (8): province, country, type, iso2, iso3, combined_key, continent_name,...
## dbl  (6): lat, long, cases, uid, code3, population
## date (1): date
## 
## i Use `spec()` to retrieve the full column specification for this data.
## i Specify the column types or set `show_col_types = FALSE` to quiet this message.
## Downloading GitHub repo RamiKrispin/coronavirus@master
##   
  
  
v  checking for file 'C:\Users\Rainy\AppData\Local\Temp\RtmpGIJ50g\remotes28a016e71cb9\RamiKrispin-coronavirus-acb5591/DESCRIPTION'
## 
  
  
  
-  preparing 'coronavirus': (1.3s)
##    checking DESCRIPTION meta-information ...
  
   checking DESCRIPTION meta-information ... 
  
v  checking DESCRIPTION meta-information
## 
  
  
  
-  checking for LF line-endings in source and make files and shell scripts (344ms)
## 
  
  
  
-  checking for empty or unneeded directories
## 
  
  
  
-  building 'coronavirus_0.3.32.tar.gz'
## 
  
   
## 
## Caught an warning!
## <simpleWarning: package 'coronavirus' is in use and will not be installed>
## `summarise()` has grouped output by 'country'. You can override using the
## `.groups` argument.

## Warning: Removed 3 row(s) containing missing values (geom_path).

Feature Extraction

With the raw data downloaded, some of the interesting features can be extracted. The first step is reconcile the time intervals. Some of the data is released monthly and some daily. I chose to interpolate all data to a daily interval. The first section of code adds the daily rows to the dataframe.

The code performs interpolation for continuous data or carries it forward for binary data like the recession indicators.

source("calcInterpolate.r")
df.data <- calcInterpolate(df.data, df.symbols)
## Warning in merge.xts(xtsData, get(df.symbols$string.symbol[idx])): NAs
## introduced by coercion

Truncate data

Create aggregate series

Some analysis requires that two or more series be combined. For example, normallizing debt by GDP to get a sense of the proportion of debt to the total economy helps understand the debt cycle.

Year over year, smoothed derivative, and log trends tend to smooth out seasonal variation. It gets used so often that I do this for every series downloaded.

source("calcFeatures.r")
lst.df <- calcFeatures(df.data, df.symbols)
## [1] "USREC has zero or negative values. Log series will be zero."
## [1] "GSFTX.Volume has zero or negative values. Log series will be zero."
## [1] "LFMIX.Volume has zero or negative values. Log series will be zero."
## [1] "LFMCX.Volume has zero or negative values. Log series will be zero."
## [1] "LFMAX.Volume has zero or negative values. Log series will be zero."
## [1] "LCSIX.Volume has zero or negative values. Log series will be zero."
## [1] "VBIRX.Volume has zero or negative values. Log series will be zero."
## [1] "VFSUX.Volume has zero or negative values. Log series will be zero."
## [1] "LTUIX.Volume has zero or negative values. Log series will be zero."
## [1] "PTTPX.Volume has zero or negative values. Log series will be zero."
## [1] "NERYX.Volume has zero or negative values. Log series will be zero."
## [1] "STIGX.Volume has zero or negative values. Log series will be zero."
## [1] "HLGAX.Volume has zero or negative values. Log series will be zero."
## [1] "FTRGX.Volume has zero or negative values. Log series will be zero."
## [1] "THIIX.Volume has zero or negative values. Log series will be zero."
## [1] "PTTRX.Volume has zero or negative values. Log series will be zero."
## [1] "BFIGX.Volume has zero or negative values. Log series will be zero."
## [1] "EIFAX.Volume has zero or negative values. Log series will be zero."
## [1] "ASDAX.Volume has zero or negative values. Log series will be zero."
## [1] "TRBUX.Volume has zero or negative values. Log series will be zero."
## [1] "PRWCX.Volume has zero or negative values. Log series will be zero."
## [1] "ADOZX.Volume has zero or negative values. Log series will be zero."
## [1] "MERFX.Volume has zero or negative values. Log series will be zero."
## [1] "CMNIX.Volume has zero or negative values. Log series will be zero."
## [1] "CIHEX.Volume has zero or negative values. Log series will be zero."
## [1] "SRPSABSNNCB has zero or negative values. Log series will be zero."
## [1] "TNX.Volume has zero or negative values. Log series will be zero."
## [1] "CLF.Open has zero or negative values. Log series will be zero."
## [1] "CLF.Low has zero or negative values. Log series will be zero."
## [1] "CLF.Close has zero or negative values. Log series will be zero."
## [1] "CLF.Volume has zero or negative values. Log series will be zero."
## [1] "CLF.Adjusted has zero or negative values. Log series will be zero."
## [1] "DTB3 has zero or negative values. Log series will be zero."
## [1] "IRX.Open has zero or negative values. Log series will be zero."
## [1] "IRX.High has zero or negative values. Log series will be zero."
## [1] "IRX.Low has zero or negative values. Log series will be zero."
## [1] "IRX.Close has zero or negative values. Log series will be zero."
## [1] "IRX.Volume has zero or negative values. Log series will be zero."
## [1] "IRX.Adjusted has zero or negative values. Log series will be zero."
## [1] "DCOILWTICO has zero or negative values. Log series will be zero."
## [1] "RLG.Volume has zero or negative values. Log series will be zero."
## [1] "STOXX50E.Volume has zero or negative values. Log series will be zero."
## [1] "GDPNOW has zero or negative values. Log series will be zero."
## [1] "W790RC1Q027SBEA has zero or negative values. Log series will be zero."
## [1] "VXX.Volume has zero or negative values. Log series will be zero."
## [1] "FYFSD has zero or negative values. Log series will be zero."
## [1] "FYFSGDA188S has zero or negative values. Log series will be zero."
## [1] "SOFR25 has zero or negative values. Log series will be zero."
## [1] "SOFR1 has zero or negative values. Log series will be zero."
## [1] "RPONTSYD has zero or negative values. Log series will be zero."
## [1] "BOPGTB has zero or negative values. Log series will be zero."
## [1] "EES.Volume has zero or negative values. Log series will be zero."
## [1] "VGSTX.Volume has zero or negative values. Log series will be zero."
## [1] "VFINX.Volume has zero or negative values. Log series will be zero."
## [1] "TMFGX.Volume has zero or negative values. Log series will be zero."
## [1] "HAINX.Volume has zero or negative values. Log series will be zero."
## [1] "IVOO.Volume has zero or negative values. Log series will be zero."
## [1] "VO.Volume has zero or negative values. Log series will be zero."
## [1] "CZA.Volume has zero or negative values. Log series will be zero."
## [1] "SLY.Volume has zero or negative values. Log series will be zero."
## [1] "HYMB.Volume has zero or negative values. Log series will be zero."
## [1] "GOLD.Open has zero or negative values. Log series will be zero."
## [1] "GOLD.Volume has zero or negative values. Log series will be zero."
## [1] "BKR.Open has zero or negative values. Log series will be zero."
## [1] "BKR.Volume has zero or negative values. Log series will be zero."
## [1] "HAL.Open has zero or negative values. Log series will be zero."
## [1] "HAL.Volume has zero or negative values. Log series will be zero."
## [1] "IP.Open has zero or negative values. Log series will be zero."
## [1] "T.Open has zero or negative values. Log series will be zero."
## [1] "OPEARNINGSPERSHARE has zero or negative values. Log series will be zero."
## [1] "AREARNINGSPERSHARE has zero or negative values. Log series will be zero."
## [1] "OCCEquityVolume has zero or negative values. Log series will be zero."
## [1] "OCCNonEquityVolume has zero or negative values. Log series will be zero."
## [1] "BUSLOANS.minus.BUSLOANSNSA has zero or negative values. Log series will be zero."
## [1] "BUSLOANS.minus.BUSLOANSNSA.by.GDP has zero or negative values. Log series will be zero."
## [1] "EXPCH.minus.IMPCH has zero or negative values. Log series will be zero."
## [1] "EXPMX.minus.IMPMX has zero or negative values. Log series will be zero."
## [1] "SRPSABSNNCB.by.GDP has zero or negative values. Log series will be zero."
## [1] "DGS30TO10 has zero or negative values. Log series will be zero."
## [1] "DGS10TO1 has zero or negative values. Log series will be zero."
## [1] "DGS10TO2 has zero or negative values. Log series will be zero."
## [1] "DGS10TOTB3MS has zero or negative values. Log series will be zero."
## [1] "DGS10TODTB3 has zero or negative values. Log series will be zero."
## [1] "DCOILWTICO.by.PPIACO has zero or negative values. Log series will be zero."
## [1] "GSPC.DailySwing has zero or negative values. Log series will be zero."
df.data <- lst.df[[1]]
df.symbols <- lst.df[[2]]

Recession calculations

Summary calculations

These values are used below

Conclusion

In this worksheet a model predicting the onset of recession was built. From the model a trading rule was derived to allow backtesting. The model performed well and the trading rule backtesting showed that applying this in the post-WWII period would have resulted in an increase in returns. That is not too bad, but there are a few changes that would likely improve the model:

Market Conditions

#The model is predicting a `r paste(sprintf("%3.0f", tail(df.data$recession.initiation.smooth.avg,1)[[1]]*100), "%", sep="")` chance of recession in the next 12 months. :

#- P/E ratio of `r sprintf("%3.2f", tail(df.data$MULTPLSP500PERATIOMONTH,1))` compares to a historical mean value over the last decade of `r sprintf("%3.2f", df.data$MULTPLSP500PERATIOMONTH_Mean[1])`. Since 2008 recession P/E has only fallen below historical norm a few times. The current value is high, but well off the peaks. If earnings are +2-4% year-over-year then it is not unrealistic.

As of Feb 2020 we have entered a recession as defined by the NBER yet the market continues to rise.

P/E ratio of 24.56 compares to a historical mean value over the last decade of 18.62. Since 2008 recession P/E has only fallen below historical norm a few times. The current value is high, but well off the peaks. If earnings are +2-4% year-over-year then it is not unrealistic.

  • S&P 500 Volume, last updated on 2022-03-24, is flat over the last year and negative over the last month.

Unemployment

  • Headline unemployment (U-3) stands at 3.80% (last updated on 2022-02-01) which is near the 1-year average of 4.73% and rising with respect to the low in the last twelve months of 3.80%. Unlikely the rate will drop again.

  • Payrolls (BLS data, NSA) year-over-year stands at 3.36% which is above the 1-year average of 5.24% and falling with respect to the peak, in the last twelve months, of 10.83%.

  • Jobless claims (ICSA data) year-over-year stands at -73.61% (last updated on 2022-03-19) which is in-line with the 1-year average of -70.99% and below the peak, in the last twelve months, of -55.13%.
## Warning: Removed 1 rows containing missing values (geom_text).
## Warning: Removed 1 rows containing missing values (geom_hline).
## Warning: Removed 1 rows containing missing values (geom_text).
## Warning: Removed 1 rows containing missing values (geom_hline).

Personal Income

  • Real personal income year over year growth stands at 1.27% (last updated on 2022-01-01). This is below the recent peak of 8.49%.

Yield Curve and Bond Market

  • The 10-year to 3-month yield stands at 1.84% (last updated on 2022-03-24). This is above the recent low of 1.14%. The trend is flat over the last year and positive over the last month.

  • Auto sales flat?

Auxillary Series

I explored additional data series. The sections below have those data series along with comments.

Recent Highs

Print out the new 180 day high values

df.symbolsTrue <-
  df.symbols[df.symbols$'Max180' == TRUE, c("string.symbol", "string.description")]
df.symbolsTrue <-
  df.symbolsTrue[!(is.na(df.symbolsTrue$string.symbol)), ]
df.symbolsTrue <-
  df.symbolsTrue[!(df.symbolsTrue$string.symbol == 'USREC'), ]
#print(head(df.symbolsTrue,20))

kable(df.symbolsTrue, caption = "6-Month High") %>%
  kable_styling(bootstrap_options = c("striped", "hover"))  
6-Month High
string.symbol string.description
1 CPIAUCSL Consumer Price Index for All Urban Consumers: All Items
4 PCEPI Personal Consumption Expenditures: Chain-type Price Index
7 NPPTTL Total Nonfarm Private Payroll Employment (ADP)
10 TABSHNO Households and nonprofit organizations; total assets, Level
11 HNONWPDPI Household Net Worth, percent Dispsable Income
12 INDPRO Industrial Production Index
14 RSALES Real Retail Sales (DISCONTINUED)
53 HSN1FNSA New One Family Houses Sold: United States (Monthly, NSA)
54 HNFSUSNSA New One Family Houses for Sale in the United States (Monthly, NSA)
55 BUSLOANS Commercial and Industrial Loans, All Commercial Banks (Monthly, SA)
57 BUSLOANSNSA Commercial and Industrial Loans, All Commercial Banks (Monthly, NSA)
58 REALLNNSA Real Estate Loans, All Commercial Banks (Monthly, NSA)
59 REALLN Real Estate Loans, All Commercial Banks (Monthly, SA)
61 RELACBW027SBOG Real Estate Loans, All Commercial Banks (Weekly, SA)
63 RREACBM027SBOG Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Monthly, SA)
64 RREACBW027SBOG Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Weekly, SA)
66 MORTGAGE30US 30-Year Fixed Rate Mortgage Average in the United States
68 TOTLLNSA Loans and Leases in Bank Credit, All Commercial Banks
70 DRCLACBS Delinquency Rate on Consumer Loans, All Commercial Banks, SA
71 TOTCINSA Commercial and Industrial Loans, All Commercial Banks (Weekly, NSA)
72 SRPSABSNNCB Nonfinancial corporate business; security repurchase agreements; asset, Level (NSA)
73 ASTLL All sectors; total loans; liability, Level (NSA)
74 FBDILNECA Domestic financial sectors; depository institution loans n.e.c.; asset, Level (NSA)
75 ASOLAL All sectors; other loans and advances; liability, Level (NSA)
76 ASTMA All sectors; total mortgages; asset, Level (NSA)
77 ASHMA All sectors; home mortgages; asset, Level (NSA)
78 ASMRMA All sectors; multifamily residential mortgages; asset, Level (NSA)
79 ASCMA All sectors; commercial mortgages; asset, Level (NSA)
80 ASFMA All sectors; farm mortgages; asset, Level (NSA)
81 CCLBSHNO Households and nonprofit organizations; consumer credit; liability, Level (NSA)
82 FBDSILQ027S Domestic financial sectors debt securities; liability, Level (NSA)
83 FBLL Domestic financial sectors loans; liability, Level (NSA)
91 TB3MS 3-Month Treasury Bill: Secondary Market Rate (Monthly)
104 GDP Gross Domestic Product
105 FNDEFX Federal Government: Nondefense Consumption Expenditures and Gross Investment (SA, Annual Rate)
108 GDPC1 Real Gross Domestic Product
109 GDPDEF Gross Domestic Product: Implicit Price Deflator
111 WLRRAL Liabilities and Capital: Liabilities: Reverse Repurchase Agreements: Wednesday Level (NSA)
112 FEDFUNDS Effective Federal Funds Rate
113 GPDI Gross Private Domestic Investment
114 W790RC1Q027SBEA Net domestic investment: Private: Domestic busines
115 MZMV Velocity of MZM Money Stock
116 M1 M1 Money Stock
117 M2 M2 Money Stock
118 OPHNFB Nonfarm Business Sector: Real Output Per Hour of All Persons
119 IPMAN Industrial Production: Manufacturing (NAICS)
121 GS5 5-Year Treasury Constant Maturity Rate
126 GFDEBTN Federal Debt: Total Public Debt
127 HOUST Housing Starts: Total: New Privately Owned Housing Units Started
131 CSUSHPINSA S&P/Case-Shiller U.S. National Home Price Index (NSA)
132 GFDEGDQ188S Federal Debt: Total Public Debt as Percent of Gross Domestic Product
133 FYFSD Federal Surplus or Deficit
134 FYFSGDA188S Federal Surplus or Deficit [-] as Percent of Gross Domestic Product
138 WALCL All Federal Reserve Banks: Total Assets
139 OUTMS Manufacturing Sector: Real Output
140 MANEMP All Employees: Manufacturing
143 AAA Moody’s Seasoned Aaa Corporate Bond Yield
146 SOFR99 Secured Overnight Financing Rate: 99th Percentile
147 SOFR75 Secured Overnight Financing Rate: 75th Percentile
150 OBFR Overnight Bank Funding Rate
151 OBFR99 Overnight Bank Funding Rate: 99th Percentile
152 OBFR75 Overnight Bank Funding Rate: 75th Percentile
153 OBFR25 Overnight Bank Funding Rate: 25th Percentile
156 IOER Interest Rate on Excess Reserves
158 EXCSRESNW Excess Reserves of Depository Institutions
159 ECBASSETS Central Bank Assets for Euro Area (11-19 Countries)
160 EUNNGDP Gross Domestic Product (Euro/ECU series) for Euro Area (19 Countries)
162 CURRENCY Currency Component of M1 (Seasonally Adjusted)
163 WCURRNS Currency Component of M1
165 PRS88003193 Nonfinancial Corporations Sector: Unit Profits
166 PPIACO Producer Price Index for All Commodities
167 PCUOMFGOMFG Producer Price Index by Industry: Total Manufacturing Industries
168 POPTHM Population (U.S.)
169 POPTHM Population (U.S.)
170 CLF16OV Civilian Labor Force Level, SA
171 LNU01000000 Civilian Labor Force Level, NSA
174 RSAFS Advance Retail Sales: Retail and Food Services
178 A065RC1A027NBEA Personal income (NSA)
179 PI Personal income (SA)
180 PCE Personal Consumption Expenditures (SA)
181 A053RC1Q027SBEA National income: Corporate profits before tax (without IVA and CCAdj)
182 CPROFIT Corporate Profits with Inventory Valuation Adjustment (IVA) and Capital Consumption Adjustment (CCAdj)
217 MULTPLSP500SALESQUARTER S&P 500 TTM Sales (Not Inflation Adjusted)
218 MULTPLSP500DIVYIELDMONTH S&P 500 Dividend Yield by Month
219 MULTPLSP500DIVMONTH S&P 500 Dividend by Month (Inflation Adjusted)
220 CHRISCMEHG1 Copper Futures, Continuous Contract #1 (HG1) (Front Month)
221 WWDIWLDISAIRGOODMTK1 Air transport, freight
223 BKRTotal Total Rig Count
224 BKRGas Gas Rig Count
225 BKROil Oil Rig Count
226 FARMINCOME Net Farm Income
227 OPEARNINGSPERSHARE Operating Earnings per Share
228 AREARNINGSPERSHARE As-Reported Earnings per Share
229 CASHDIVIDENDSPERSHR Cash Dividends per Share
230 SALESPERSHR Sales per Share
231 BOOKVALPERSHR Book value per Share
232 CAPEXPERSHR Cap ex per Share
233 PRICE Price
234 OPEARNINGSTTM TTM Operating Earnings
235 AREARNINGSTTM TTM Reported Earnings
237 FINRAFreeCreditMargin Free Credit Balances in Customers’ Securities Margin Accounts
238 OCCEquityVolume Equity Options Volume
239 OCCNonEquityVolume Non-Equity Options Volume
243 BUSLOANS.by.GDP Business Loans Normalized by GDP
246 BUSLOANSNSA.by.GDP Business Loans Normalized by GDP
248 TOTCINSA.by.GDP Business Loans (Weekly, NSA) Normalized by GDP
253 PI.by.GDP Personal Income (SA) Normalized by GDP
258 RREACBM027SBOG.by.GDP Residental Real Estate Loans (Monthly, SA) divided by GDP
259 RREACBW027SBOG.by.GDP Residental Real Estate Loans (Weekly, SA) divided by GDP
264 ASHMA.INTEREST Home Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens
268 TOTLNNSA Total Loans Not Seasonally Adjusted (BUSLOANS+REALLNSA+CONSUMERNSA)
269 TOTLNNSA.by.GDP Total Loans Not Seasonally Adjusted divided by GDP
274 WLRRAL.by.GDP Liabilities and Capital: Liabilities: Reverse Repurchase Agreements: Wednesday Level (NSA) Divided by GDP
278 SRPSABSNNCB.by.GDP Nonfinancial corporate business; security repurchase agreements; asset, Level (NSA) Divided by GDP
282 ASFMA.INTEREST Farm Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens
283 ASFMA.INTEREST.by.GDP Farm Mortgages (Quarterly, NSA) Interest Burden Divided by GDP
286 WALCL.by.GDP All Federal Reserve Banks: Total Assets Divided by GDP
296 NPPTTLBYPOPTHM ADP Private Employment / Population
316 MSPUS.times.HOUST New privately owned units start times median price
317 MSPUS.times.HNFSUSNSA New privately owned 1-family units for sale times median price
321 CPIAUCSL_Smooth Savitsky-Golay Smoothed (p=3, n=365) Consumer Price Index for All Urban Consumers: All Items
324 CPIAUCSL_Log Log of Consumer Price Index for All Urban Consumers: All Items
325 CPIAUCSL_mva200 Consumer Price Index for All Urban Consumers: All Items 200 Day MA
326 CPIAUCSL_mva050 Consumer Price Index for All Urban Consumers: All Items 50 Day MA
327 USREC_YoY NBER based Recession Indicators Year over Year
328 USREC_YoY4 NBER based Recession Indicators 4 Year over 4 Year
329 USREC_YoY5 NBER based Recession Indicators 5 Year over 5 Year
330 USREC_Smooth Savitsky-Golay Smoothed (p=3, n=365) NBER based Recession Indicators
331 USREC_Smooth.short Savitsky-Golay Smoothed (p=3, n=15) NBER based Recession Indicators
332 USREC_SmoothDer Derivative of Smoothed NBER based Recession Indicators
333 USREC_Log Log of NBER based Recession Indicators
334 USREC_mva200 NBER based Recession Indicators 200 Day MA
335 USREC_mva050 NBER based Recession Indicators 50 Day MA
341 UNRATE_SmoothDer Derivative of Smoothed Civilian Unemployment Rate U-3
351 PCEPI_Log Log of Personal Consumption Expenditures: Chain-type Price Index
352 PCEPI_mva200 Personal Consumption Expenditures: Chain-type Price Index 200 Day MA
353 PCEPI_mva050 Personal Consumption Expenditures: Chain-type Price Index 50 Day MA
354 CCSA_YoY Continued Claims (Insured Unemployment) Year over Year
363 CCNSA_YoY Continued Claims (Insured Unemployment, NSA) Year over Year
368 CCNSA_SmoothDer Derivative of Smoothed Continued Claims (Insured Unemployment, NSA)
375 NPPTTL_Smooth Savitsky-Golay Smoothed (p=3, n=365) Total Nonfarm Private Payroll Employment (ADP)
378 NPPTTL_Log Log of Total Nonfarm Private Payroll Employment (ADP)
379 NPPTTL_mva200 Total Nonfarm Private Payroll Employment (ADP) 200 Day MA
380 NPPTTL_mva050 Total Nonfarm Private Payroll Employment (ADP) 50 Day MA
381 U6RATE_YoY Total unemployed + margin + part-time U-6 Year over Year
386 U6RATE_SmoothDer Derivative of Smoothed Total unemployed + margin + part-time U-6
397 PAYNSA_mva200 All Employees: Total Nonfarm Payrolls (NSA) 200 Day MA
405 TABSHNO_Log Log of Households and nonprofit organizations; total assets, Level
406 TABSHNO_mva200 Households and nonprofit organizations; total assets, Level 200 Day MA
407 TABSHNO_mva050 Households and nonprofit organizations; total assets, Level 50 Day MA
409 HNONWPDPI_YoY4 Household Net Worth, percent Dispsable Income 4 Year over 4 Year
414 HNONWPDPI_Log Log of Household Net Worth, percent Dispsable Income
415 HNONWPDPI_mva200 Household Net Worth, percent Dispsable Income 200 Day MA
416 HNONWPDPI_mva050 Household Net Worth, percent Dispsable Income 50 Day MA
420 INDPRO_Smooth Savitsky-Golay Smoothed (p=3, n=365) Industrial Production Index
422 INDPRO_SmoothDer Derivative of Smoothed Industrial Production Index
423 INDPRO_Log Log of Industrial Production Index
424 INDPRO_mva200 Industrial Production Index 200 Day MA
425 INDPRO_mva050 Industrial Production Index 50 Day MA
429 RRSFS_Smooth Savitsky-Golay Smoothed (p=3, n=365) Real Retail and Food Services Sales
431 RRSFS_SmoothDer Derivative of Smoothed Real Retail and Food Services Sales
435 RSALES_YoY Real Retail Sales (DISCONTINUED) Year over Year
436 RSALES_YoY4 Real Retail Sales (DISCONTINUED) 4 Year over 4 Year
437 RSALES_YoY5 Real Retail Sales (DISCONTINUED) 5 Year over 5 Year
441 RSALES_Log Log of Real Retail Sales (DISCONTINUED)
442 RSALES_mva200 Real Retail Sales (DISCONTINUED) 200 Day MA
443 RSALES_mva050 Real Retail Sales (DISCONTINUED) 50 Day MA
458 RPI_SmoothDer Derivative of Smoothed Real personal income
467 PCOPPUSDM_SmoothDer Derivative of Smoothed Global price of Copper
469 PCOPPUSDM_mva200 Global price of Copper 200 Day MA
510 NOBL.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
512 NOBL.Volume_SmoothDer Derivative of Smoothed
514 NOBL.Volume_mva200 200 Day MA
541 SCHD.High_mva200 200 Day MA
564 SCHD.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
566 SCHD.Volume_SmoothDer Derivative of Smoothed
568 SCHD.Volume_mva200 200 Day MA
577 SCHD.Adjusted_mva200 200 Day MA
620 PFF.Volume_SmoothDer Derivative of Smoothed
672 HPI.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
674 HPI.Volume_SmoothDer Derivative of Smoothed
723 GSFTX.Volume_YoY Year over Year
724 GSFTX.Volume_YoY4 4 Year over 4 Year
725 GSFTX.Volume_YoY5 5 Year over 5 Year
726 GSFTX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
727 GSFTX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
728 GSFTX.Volume_SmoothDer Derivative of Smoothed
729 GSFTX.Volume_Log Log of
730 GSFTX.Volume_mva200 200 Day MA
731 GSFTX.Volume_mva050 50 Day MA
739 GSFTX.Adjusted_mva200 200 Day MA
746 LFMIX.Open_SmoothDer Derivative of Smoothed
755 LFMIX.High_SmoothDer Derivative of Smoothed
764 LFMIX.Low_SmoothDer Derivative of Smoothed
773 LFMIX.Close_SmoothDer Derivative of Smoothed
777 LFMIX.Volume_YoY Year over Year
778 LFMIX.Volume_YoY4 4 Year over 4 Year
779 LFMIX.Volume_YoY5 5 Year over 5 Year
780 LFMIX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
781 LFMIX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
782 LFMIX.Volume_SmoothDer Derivative of Smoothed
783 LFMIX.Volume_Log Log of
784 LFMIX.Volume_mva200 200 Day MA
785 LFMIX.Volume_mva050 50 Day MA
789 LFMIX.Adjusted_Smooth Savitsky-Golay Smoothed (p=3, n=365)
790 LFMIX.Adjusted_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
791 LFMIX.Adjusted_SmoothDer Derivative of Smoothed
792 LFMIX.Adjusted_Log Log of
794 LFMIX.Adjusted_mva050 50 Day MA
799 LFMCX.Open_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
800 LFMCX.Open_SmoothDer Derivative of Smoothed
808 LFMCX.High_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
809 LFMCX.High_SmoothDer Derivative of Smoothed
817 LFMCX.Low_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
818 LFMCX.Low_SmoothDer Derivative of Smoothed
826 LFMCX.Close_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
827 LFMCX.Close_SmoothDer Derivative of Smoothed
831 LFMCX.Volume_YoY Year over Year
832 LFMCX.Volume_YoY4 4 Year over 4 Year
833 LFMCX.Volume_YoY5 5 Year over 5 Year
834 LFMCX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
835 LFMCX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
836 LFMCX.Volume_SmoothDer Derivative of Smoothed
837 LFMCX.Volume_Log Log of
838 LFMCX.Volume_mva200 200 Day MA
839 LFMCX.Volume_mva050 50 Day MA
843 LFMCX.Adjusted_Smooth Savitsky-Golay Smoothed (p=3, n=365)
844 LFMCX.Adjusted_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
845 LFMCX.Adjusted_SmoothDer Derivative of Smoothed
846 LFMCX.Adjusted_Log Log of
848 LFMCX.Adjusted_mva050 50 Day MA
853 LFMAX.Open_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
854 LFMAX.Open_SmoothDer Derivative of Smoothed
862 LFMAX.High_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
863 LFMAX.High_SmoothDer Derivative of Smoothed
871 LFMAX.Low_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
872 LFMAX.Low_SmoothDer Derivative of Smoothed
880 LFMAX.Close_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
881 LFMAX.Close_SmoothDer Derivative of Smoothed
885 LFMAX.Volume_YoY Year over Year
886 LFMAX.Volume_YoY4 4 Year over 4 Year
887 LFMAX.Volume_YoY5 5 Year over 5 Year
888 LFMAX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
889 LFMAX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
890 LFMAX.Volume_SmoothDer Derivative of Smoothed
891 LFMAX.Volume_Log Log of
892 LFMAX.Volume_mva200 200 Day MA
893 LFMAX.Volume_mva050 50 Day MA
897 LFMAX.Adjusted_Smooth Savitsky-Golay Smoothed (p=3, n=365)
898 LFMAX.Adjusted_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
899 LFMAX.Adjusted_SmoothDer Derivative of Smoothed
900 LFMAX.Adjusted_Log Log of
902 LFMAX.Adjusted_mva050 50 Day MA
906 LCSIX.Open_Smooth Savitsky-Golay Smoothed (p=3, n=365)
910 LCSIX.Open_mva200 200 Day MA
915 LCSIX.High_Smooth Savitsky-Golay Smoothed (p=3, n=365)
919 LCSIX.High_mva200 200 Day MA
924 LCSIX.Low_Smooth Savitsky-Golay Smoothed (p=3, n=365)
928 LCSIX.Low_mva200 200 Day MA
933 LCSIX.Close_Smooth Savitsky-Golay Smoothed (p=3, n=365)
937 LCSIX.Close_mva200 200 Day MA
939 LCSIX.Volume_YoY Year over Year
940 LCSIX.Volume_YoY4 4 Year over 4 Year
941 LCSIX.Volume_YoY5 5 Year over 5 Year
942 LCSIX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
943 LCSIX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
944 LCSIX.Volume_SmoothDer Derivative of Smoothed
945 LCSIX.Volume_Log Log of
946 LCSIX.Volume_mva200 200 Day MA
947 LCSIX.Volume_mva050 50 Day MA
948 LCSIX.Adjusted_YoY Year over Year
951 LCSIX.Adjusted_Smooth Savitsky-Golay Smoothed (p=3, n=365)
953 LCSIX.Adjusted_SmoothDer Derivative of Smoothed
955 LCSIX.Adjusted_mva200 200 Day MA
956 LCSIX.Adjusted_mva050 50 Day MA
996 BSV.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
997 BSV.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
998 BSV.Volume_SmoothDer Derivative of Smoothed
1047 VBIRX.Volume_YoY Year over Year
1048 VBIRX.Volume_YoY4 4 Year over 4 Year
1049 VBIRX.Volume_YoY5 5 Year over 5 Year
1050 VBIRX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
1051 VBIRX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
1052 VBIRX.Volume_SmoothDer Derivative of Smoothed
1053 VBIRX.Volume_Log Log of
1054 VBIRX.Volume_mva200 200 Day MA
1055 VBIRX.Volume_mva050 50 Day MA
1104 BIV.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
1106 BIV.Volume_SmoothDer Derivative of Smoothed
1108 BIV.Volume_mva200 200 Day MA
1155 VFSUX.Volume_YoY Year over Year
1156 VFSUX.Volume_YoY4 4 Year over 4 Year
1157 VFSUX.Volume_YoY5 5 Year over 5 Year
1158 VFSUX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
1159 VFSUX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
1160 VFSUX.Volume_SmoothDer Derivative of Smoothed
1161 VFSUX.Volume_Log Log of
1162 VFSUX.Volume_mva200 200 Day MA
1163 VFSUX.Volume_mva050 50 Day MA
1209 LTUIX.Volume_YoY Year over Year
1210 LTUIX.Volume_YoY4 4 Year over 4 Year
1211 LTUIX.Volume_YoY5 5 Year over 5 Year
1212 LTUIX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
1213 LTUIX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
1214 LTUIX.Volume_SmoothDer Derivative of Smoothed
1215 LTUIX.Volume_Log Log of
1216 LTUIX.Volume_mva200 200 Day MA
1217 LTUIX.Volume_mva050 50 Day MA
1263 PTTPX.Volume_YoY Year over Year
1264 PTTPX.Volume_YoY4 4 Year over 4 Year
1265 PTTPX.Volume_YoY5 5 Year over 5 Year
1266 PTTPX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
1267 PTTPX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
1268 PTTPX.Volume_SmoothDer Derivative of Smoothed
1269 PTTPX.Volume_Log Log of
1270 PTTPX.Volume_mva200 200 Day MA
1271 PTTPX.Volume_mva050 50 Day MA
1317 NERYX.Volume_YoY Year over Year
1318 NERYX.Volume_YoY4 4 Year over 4 Year
1319 NERYX.Volume_YoY5 5 Year over 5 Year
1320 NERYX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
1321 NERYX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
1322 NERYX.Volume_SmoothDer Derivative of Smoothed
1323 NERYX.Volume_Log Log of
1324 NERYX.Volume_mva200 200 Day MA
1325 NERYX.Volume_mva050 50 Day MA
1371 STIGX.Volume_YoY Year over Year
1372 STIGX.Volume_YoY4 4 Year over 4 Year
1373 STIGX.Volume_YoY5 5 Year over 5 Year
1374 STIGX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
1375 STIGX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
1376 STIGX.Volume_SmoothDer Derivative of Smoothed
1377 STIGX.Volume_Log Log of
1378 STIGX.Volume_mva200 200 Day MA
1379 STIGX.Volume_mva050 50 Day MA
1425 HLGAX.Volume_YoY Year over Year
1426 HLGAX.Volume_YoY4 4 Year over 4 Year
1427 HLGAX.Volume_YoY5 5 Year over 5 Year
1428 HLGAX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
1429 HLGAX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
1430 HLGAX.Volume_SmoothDer Derivative of Smoothed
1431 HLGAX.Volume_Log Log of
1432 HLGAX.Volume_mva200 200 Day MA
1433 HLGAX.Volume_mva050 50 Day MA
1479 FTRGX.Volume_YoY Year over Year
1480 FTRGX.Volume_YoY4 4 Year over 4 Year
1481 FTRGX.Volume_YoY5 5 Year over 5 Year
1482 FTRGX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
1483 FTRGX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
1484 FTRGX.Volume_SmoothDer Derivative of Smoothed
1485 FTRGX.Volume_Log Log of
1486 FTRGX.Volume_mva200 200 Day MA
1487 FTRGX.Volume_mva050 50 Day MA
1533 THIIX.Volume_YoY Year over Year
1534 THIIX.Volume_YoY4 4 Year over 4 Year
1535 THIIX.Volume_YoY5 5 Year over 5 Year
1536 THIIX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
1537 THIIX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
1538 THIIX.Volume_SmoothDer Derivative of Smoothed
1539 THIIX.Volume_Log Log of
1540 THIIX.Volume_mva200 200 Day MA
1541 THIIX.Volume_mva050 50 Day MA
1587 PTTRX.Volume_YoY Year over Year
1588 PTTRX.Volume_YoY4 4 Year over 4 Year
1589 PTTRX.Volume_YoY5 5 Year over 5 Year
1590 PTTRX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
1591 PTTRX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
1592 PTTRX.Volume_SmoothDer Derivative of Smoothed
1593 PTTRX.Volume_Log Log of
1594 PTTRX.Volume_mva200 200 Day MA
1595 PTTRX.Volume_mva050 50 Day MA
1641 BFIGX.Volume_YoY Year over Year
1642 BFIGX.Volume_YoY4 4 Year over 4 Year
1643 BFIGX.Volume_YoY5 5 Year over 5 Year
1644 BFIGX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
1645 BFIGX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
1646 BFIGX.Volume_SmoothDer Derivative of Smoothed
1647 BFIGX.Volume_Log Log of
1648 BFIGX.Volume_mva200 200 Day MA
1649 BFIGX.Volume_mva050 50 Day MA
1702 VTWO.Volume_mva200 200 Day MA
1749 EIFAX.Volume_YoY Year over Year
1750 EIFAX.Volume_YoY4 4 Year over 4 Year
1751 EIFAX.Volume_YoY5 5 Year over 5 Year
1752 EIFAX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
1753 EIFAX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
1754 EIFAX.Volume_SmoothDer Derivative of Smoothed
1755 EIFAX.Volume_Log Log of
1756 EIFAX.Volume_mva200 200 Day MA
1757 EIFAX.Volume_mva050 50 Day MA
1803 ASDAX.Volume_YoY Year over Year
1804 ASDAX.Volume_YoY4 4 Year over 4 Year
1805 ASDAX.Volume_YoY5 5 Year over 5 Year
1806 ASDAX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
1807 ASDAX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
1808 ASDAX.Volume_SmoothDer Derivative of Smoothed
1809 ASDAX.Volume_Log Log of
1810 ASDAX.Volume_mva200 200 Day MA
1811 ASDAX.Volume_mva050 50 Day MA
1857 TRBUX.Volume_YoY Year over Year
1858 TRBUX.Volume_YoY4 4 Year over 4 Year
1859 TRBUX.Volume_YoY5 5 Year over 5 Year
1860 TRBUX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
1861 TRBUX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
1862 TRBUX.Volume_SmoothDer Derivative of Smoothed
1863 TRBUX.Volume_Log Log of
1864 TRBUX.Volume_mva200 200 Day MA
1865 TRBUX.Volume_mva050 50 Day MA
1911 PRWCX.Volume_YoY Year over Year
1912 PRWCX.Volume_YoY4 4 Year over 4 Year
1913 PRWCX.Volume_YoY5 5 Year over 5 Year
1914 PRWCX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
1915 PRWCX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
1916 PRWCX.Volume_SmoothDer Derivative of Smoothed
1917 PRWCX.Volume_Log Log of
1918 PRWCX.Volume_mva200 200 Day MA
1919 PRWCX.Volume_mva050 50 Day MA
1965 ADOZX.Volume_YoY Year over Year
1966 ADOZX.Volume_YoY4 4 Year over 4 Year
1967 ADOZX.Volume_YoY5 5 Year over 5 Year
1968 ADOZX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
1969 ADOZX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
1970 ADOZX.Volume_SmoothDer Derivative of Smoothed
1971 ADOZX.Volume_Log Log of
1972 ADOZX.Volume_mva200 200 Day MA
1973 ADOZX.Volume_mva050 50 Day MA
1986 MERFX.Open_Smooth Savitsky-Golay Smoothed (p=3, n=365)
1988 MERFX.Open_SmoothDer Derivative of Smoothed
1995 MERFX.High_Smooth Savitsky-Golay Smoothed (p=3, n=365)
1997 MERFX.High_SmoothDer Derivative of Smoothed
2004 MERFX.Low_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2006 MERFX.Low_SmoothDer Derivative of Smoothed
2013 MERFX.Close_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2015 MERFX.Close_SmoothDer Derivative of Smoothed
2019 MERFX.Volume_YoY Year over Year
2020 MERFX.Volume_YoY4 4 Year over 4 Year
2021 MERFX.Volume_YoY5 5 Year over 5 Year
2022 MERFX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2023 MERFX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
2024 MERFX.Volume_SmoothDer Derivative of Smoothed
2025 MERFX.Volume_Log Log of
2026 MERFX.Volume_mva200 200 Day MA
2027 MERFX.Volume_mva050 50 Day MA
2031 MERFX.Adjusted_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2033 MERFX.Adjusted_SmoothDer Derivative of Smoothed
2073 CMNIX.Volume_YoY Year over Year
2074 CMNIX.Volume_YoY4 4 Year over 4 Year
2075 CMNIX.Volume_YoY5 5 Year over 5 Year
2076 CMNIX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2077 CMNIX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
2078 CMNIX.Volume_SmoothDer Derivative of Smoothed
2079 CMNIX.Volume_Log Log of
2080 CMNIX.Volume_mva200 200 Day MA
2081 CMNIX.Volume_mva050 50 Day MA
2127 CIHEX.Volume_YoY Year over Year
2128 CIHEX.Volume_YoY4 4 Year over 4 Year
2129 CIHEX.Volume_YoY5 5 Year over 5 Year
2130 CIHEX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2131 CIHEX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
2132 CIHEX.Volume_SmoothDer Derivative of Smoothed
2133 CIHEX.Volume_Log Log of
2134 CIHEX.Volume_mva200 200 Day MA
2135 CIHEX.Volume_mva050 50 Day MA
2146 IMPCH_YoY4 U.S. Imports of Goods by Customs Basis from China (Monthly, NSA) 4 Year over 4 Year
2152 IMPCH_mva200 U.S. Imports of Goods by Customs Basis from China (Monthly, NSA) 200 Day MA
2170 IMPMX_mva200 U.S. Imports of Goods by Customs Basis from Mexico (Monthly, NSA) 200 Day MA
2177 EXPMX_SmoothDer Derivative of Smoothed U.S. Exports of Goods by F.A.S. Basis to Mexico (Monthly, NSA)
2184 HSN1FNSA_Smooth Savitsky-Golay Smoothed (p=3, n=365) New One Family Houses Sold: United States (Monthly, NSA)
2186 HSN1FNSA_SmoothDer Derivative of Smoothed New One Family Houses Sold: United States (Monthly, NSA)
2187 HSN1FNSA_Log Log of New One Family Houses Sold: United States (Monthly, NSA)
2189 HSN1FNSA_mva050 New One Family Houses Sold: United States (Monthly, NSA) 50 Day MA
2193 HNFSUSNSA_Smooth Savitsky-Golay Smoothed (p=3, n=365) New One Family Houses for Sale in the United States (Monthly, NSA)
2196 HNFSUSNSA_Log Log of New One Family Houses for Sale in the United States (Monthly, NSA)
2197 HNFSUSNSA_mva200 New One Family Houses for Sale in the United States (Monthly, NSA) 200 Day MA
2198 HNFSUSNSA_mva050 New One Family Houses for Sale in the United States (Monthly, NSA) 50 Day MA
2199 BUSLOANS_YoY Commercial and Industrial Loans, All Commercial Banks (Monthly, SA) Year over Year
2204 BUSLOANS_SmoothDer Derivative of Smoothed Commercial and Industrial Loans, All Commercial Banks (Monthly, SA)
2205 BUSLOANS_Log Log of Commercial and Industrial Loans, All Commercial Banks (Monthly, SA)
2207 BUSLOANS_mva050 Commercial and Industrial Loans, All Commercial Banks (Monthly, SA) 50 Day MA
2208 TOTCI_YoY Commercial and Industrial Loans, All Commercial Banks (Weekly, SA) Year over Year
2210 TOTCI_YoY5 Commercial and Industrial Loans, All Commercial Banks (Weekly, SA) 5 Year over 5 Year
2211 TOTCI_Smooth Savitsky-Golay Smoothed (p=3, n=365) Commercial and Industrial Loans, All Commercial Banks (Weekly, SA)
2213 TOTCI_SmoothDer Derivative of Smoothed Commercial and Industrial Loans, All Commercial Banks (Weekly, SA)
2216 TOTCI_mva050 Commercial and Industrial Loans, All Commercial Banks (Weekly, SA) 50 Day MA
2220 BUSLOANSNSA_Smooth Savitsky-Golay Smoothed (p=3, n=365) Commercial and Industrial Loans, All Commercial Banks (Monthly, NSA)
2222 BUSLOANSNSA_SmoothDer Derivative of Smoothed Commercial and Industrial Loans, All Commercial Banks (Monthly, NSA)
2223 BUSLOANSNSA_Log Log of Commercial and Industrial Loans, All Commercial Banks (Monthly, NSA)
2225 BUSLOANSNSA_mva050 Commercial and Industrial Loans, All Commercial Banks (Monthly, NSA) 50 Day MA
2232 REALLNNSA_Log Log of Real Estate Loans, All Commercial Banks (Monthly, NSA)
2233 REALLNNSA_mva200 Real Estate Loans, All Commercial Banks (Monthly, NSA) 200 Day MA
2234 REALLNNSA_mva050 Real Estate Loans, All Commercial Banks (Monthly, NSA) 50 Day MA
2238 REALLN_Smooth Savitsky-Golay Smoothed (p=3, n=365) Real Estate Loans, All Commercial Banks (Monthly, SA)
2241 REALLN_Log Log of Real Estate Loans, All Commercial Banks (Monthly, SA)
2242 REALLN_mva200 Real Estate Loans, All Commercial Banks (Monthly, SA) 200 Day MA
2243 REALLN_mva050 Real Estate Loans, All Commercial Banks (Monthly, SA) 50 Day MA
2251 RELACBW027NBOG_mva200 Real Estate Loans, All Commercial Banks (Weekly, NSA) 200 Day MA
2252 RELACBW027NBOG_mva050 Real Estate Loans, All Commercial Banks (Weekly, NSA) 50 Day MA
2256 RELACBW027SBOG_Smooth Savitsky-Golay Smoothed (p=3, n=365) Real Estate Loans, All Commercial Banks (Weekly, SA)
2258 RELACBW027SBOG_SmoothDer Derivative of Smoothed Real Estate Loans, All Commercial Banks (Weekly, SA)
2259 RELACBW027SBOG_Log Log of Real Estate Loans, All Commercial Banks (Weekly, SA)
2260 RELACBW027SBOG_mva200 Real Estate Loans, All Commercial Banks (Weekly, SA) 200 Day MA
2261 RELACBW027SBOG_mva050 Real Estate Loans, All Commercial Banks (Weekly, SA) 50 Day MA
2262 RREACBM027NBOG_YoY Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Monthly, NSA) Year over Year
2269 RREACBM027NBOG_mva200 Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Monthly, NSA) 200 Day MA
2271 RREACBM027SBOG_YoY Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Monthly, SA) Year over Year
2277 RREACBM027SBOG_Log Log of Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Monthly, SA)
2278 RREACBM027SBOG_mva200 Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Monthly, SA) 200 Day MA
2279 RREACBM027SBOG_mva050 Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Monthly, SA) 50 Day MA
2283 RREACBW027SBOG_Smooth Savitsky-Golay Smoothed (p=3, n=365) Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Weekly, SA)
2285 RREACBW027SBOG_SmoothDer Derivative of Smoothed Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Weekly, SA)
2286 RREACBW027SBOG_Log Log of Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Weekly, SA)
2287 RREACBW027SBOG_mva200 Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Weekly, SA) 200 Day MA
2288 RREACBW027SBOG_mva050 Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Weekly, SA) 50 Day MA
2296 RREACBW027NBOG_mva200 Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Weekly, NSA) 200 Day MA
2297 RREACBW027NBOG_mva050 Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Weekly, NSA) 50 Day MA
2299 MORTGAGE30US_YoY4 30-Year Fixed Rate Mortgage Average in the United States 4 Year over 4 Year
2300 MORTGAGE30US_YoY5 30-Year Fixed Rate Mortgage Average in the United States 5 Year over 5 Year
2301 MORTGAGE30US_Smooth Savitsky-Golay Smoothed (p=3, n=365) 30-Year Fixed Rate Mortgage Average in the United States
2302 MORTGAGE30US_Smooth.short Savitsky-Golay Smoothed (p=3, n=15) 30-Year Fixed Rate Mortgage Average in the United States
2303 MORTGAGE30US_SmoothDer Derivative of Smoothed 30-Year Fixed Rate Mortgage Average in the United States
2304 MORTGAGE30US_Log Log of 30-Year Fixed Rate Mortgage Average in the United States
2305 MORTGAGE30US_mva200 30-Year Fixed Rate Mortgage Average in the United States 200 Day MA
2306 MORTGAGE30US_mva050 30-Year Fixed Rate Mortgage Average in the United States 50 Day MA
2314 CONSUMERNSA_mva200 Consumer Loans, All Commercial Banks 200 Day MA
2319 TOTLLNSA_Smooth Savitsky-Golay Smoothed (p=3, n=365) Loans and Leases in Bank Credit, All Commercial Banks
2321 TOTLLNSA_SmoothDer Derivative of Smoothed Loans and Leases in Bank Credit, All Commercial Banks
2322 TOTLLNSA_Log Log of Loans and Leases in Bank Credit, All Commercial Banks
2323 TOTLLNSA_mva200 Loans and Leases in Bank Credit, All Commercial Banks 200 Day MA
2324 TOTLLNSA_mva050 Loans and Leases in Bank Credit, All Commercial Banks 50 Day MA
2328 DPSACBW027SBOG_Smooth Savitsky-Golay Smoothed (p=3, n=365) Deposits, All Commercial Banks
2332 DPSACBW027SBOG_mva200 Deposits, All Commercial Banks 200 Day MA
2333 DPSACBW027SBOG_mva050 Deposits, All Commercial Banks 50 Day MA
2334 DRCLACBS_YoY Delinquency Rate on Consumer Loans, All Commercial Banks, SA Year over Year
2335 DRCLACBS_YoY4 Delinquency Rate on Consumer Loans, All Commercial Banks, SA 4 Year over 4 Year
2336 DRCLACBS_YoY5 Delinquency Rate on Consumer Loans, All Commercial Banks, SA 5 Year over 5 Year
2340 DRCLACBS_Log Log of Delinquency Rate on Consumer Loans, All Commercial Banks, SA
2341 DRCLACBS_mva200 Delinquency Rate on Consumer Loans, All Commercial Banks, SA 200 Day MA
2342 DRCLACBS_mva050 Delinquency Rate on Consumer Loans, All Commercial Banks, SA 50 Day MA
2346 TOTCINSA_Smooth Savitsky-Golay Smoothed (p=3, n=365) Commercial and Industrial Loans, All Commercial Banks (Weekly, NSA)
2348 TOTCINSA_SmoothDer Derivative of Smoothed Commercial and Industrial Loans, All Commercial Banks (Weekly, NSA)
2349 TOTCINSA_Log Log of Commercial and Industrial Loans, All Commercial Banks (Weekly, NSA)
2351 TOTCINSA_mva050 Commercial and Industrial Loans, All Commercial Banks (Weekly, NSA) 50 Day MA
2353 SRPSABSNNCB_YoY4 Nonfinancial corporate business; security repurchase agreements; asset, Level (NSA) 4 Year over 4 Year
2354 SRPSABSNNCB_YoY5 Nonfinancial corporate business; security repurchase agreements; asset, Level (NSA) 5 Year over 5 Year
2357 SRPSABSNNCB_SmoothDer Derivative of Smoothed Nonfinancial corporate business; security repurchase agreements; asset, Level (NSA)
2358 SRPSABSNNCB_Log Log of Nonfinancial corporate business; security repurchase agreements; asset, Level (NSA)
2359 SRPSABSNNCB_mva200 Nonfinancial corporate business; security repurchase agreements; asset, Level (NSA) 200 Day MA
2360 SRPSABSNNCB_mva050 Nonfinancial corporate business; security repurchase agreements; asset, Level (NSA) 50 Day MA
2367 ASTLL_Log Log of All sectors; total loans; liability, Level (NSA)
2368 ASTLL_mva200 All sectors; total loans; liability, Level (NSA) 200 Day MA
2369 ASTLL_mva050 All sectors; total loans; liability, Level (NSA) 50 Day MA
2370 FBDILNECA_YoY Domestic financial sectors; depository institution loans n.e.c.; asset, Level (NSA) Year over Year
2376 FBDILNECA_Log Log of Domestic financial sectors; depository institution loans n.e.c.; asset, Level (NSA)
2377 FBDILNECA_mva200 Domestic financial sectors; depository institution loans n.e.c.; asset, Level (NSA) 200 Day MA
2378 FBDILNECA_mva050 Domestic financial sectors; depository institution loans n.e.c.; asset, Level (NSA) 50 Day MA
2382 ASOLAL_Smooth Savitsky-Golay Smoothed (p=3, n=365) All sectors; other loans and advances; liability, Level (NSA)
2385 ASOLAL_Log Log of All sectors; other loans and advances; liability, Level (NSA)
2386 ASOLAL_mva200 All sectors; other loans and advances; liability, Level (NSA) 200 Day MA
2387 ASOLAL_mva050 All sectors; other loans and advances; liability, Level (NSA) 50 Day MA
2394 ASTMA_Log Log of All sectors; total mortgages; asset, Level (NSA)
2395 ASTMA_mva200 All sectors; total mortgages; asset, Level (NSA) 200 Day MA
2396 ASTMA_mva050 All sectors; total mortgages; asset, Level (NSA) 50 Day MA
2403 ASHMA_Log Log of All sectors; home mortgages; asset, Level (NSA)
2404 ASHMA_mva200 All sectors; home mortgages; asset, Level (NSA) 200 Day MA
2405 ASHMA_mva050 All sectors; home mortgages; asset, Level (NSA) 50 Day MA
2412 ASMRMA_Log Log of All sectors; multifamily residential mortgages; asset, Level (NSA)
2413 ASMRMA_mva200 All sectors; multifamily residential mortgages; asset, Level (NSA) 200 Day MA
2414 ASMRMA_mva050 All sectors; multifamily residential mortgages; asset, Level (NSA) 50 Day MA
2421 ASCMA_Log Log of All sectors; commercial mortgages; asset, Level (NSA)
2422 ASCMA_mva200 All sectors; commercial mortgages; asset, Level (NSA) 200 Day MA
2423 ASCMA_mva050 All sectors; commercial mortgages; asset, Level (NSA) 50 Day MA
2430 ASFMA_Log Log of All sectors; farm mortgages; asset, Level (NSA)
2431 ASFMA_mva200 All sectors; farm mortgages; asset, Level (NSA) 200 Day MA
2432 ASFMA_mva050 All sectors; farm mortgages; asset, Level (NSA) 50 Day MA
2439 CCLBSHNO_Log Log of Households and nonprofit organizations; consumer credit; liability, Level (NSA)
2440 CCLBSHNO_mva200 Households and nonprofit organizations; consumer credit; liability, Level (NSA) 200 Day MA
2441 CCLBSHNO_mva050 Households and nonprofit organizations; consumer credit; liability, Level (NSA) 50 Day MA
2448 FBDSILQ027S_Log Log of Domestic financial sectors debt securities; liability, Level (NSA)
2449 FBDSILQ027S_mva200 Domestic financial sectors debt securities; liability, Level (NSA) 200 Day MA
2450 FBDSILQ027S_mva050 Domestic financial sectors debt securities; liability, Level (NSA) 50 Day MA
2457 FBLL_Log Log of Domestic financial sectors loans; liability, Level (NSA)
2458 FBLL_mva200 Domestic financial sectors loans; liability, Level (NSA) 200 Day MA
2459 FBLL_mva050 Domestic financial sectors loans; liability, Level (NSA) 50 Day MA
2463 NCBDBIQ027S_Smooth Savitsky-Golay Smoothed (p=3, n=365) Nonfinancial corporate business; debt securities; liability, Level
2472 DGS10_Smooth Savitsky-Golay Smoothed (p=3, n=365) 10-Year Treasury Constant Maturity Rate
2473 DGS10_Smooth.short Savitsky-Golay Smoothed (p=3, n=15) 10-Year Treasury Constant Maturity Rate
2474 DGS10_SmoothDer Derivative of Smoothed 10-Year Treasury Constant Maturity Rate
2476 DGS10_mva200 10-Year Treasury Constant Maturity Rate 200 Day MA
2477 DGS10_mva050 10-Year Treasury Constant Maturity Rate 50 Day MA
2480 TNX.Open_YoY5 5 Year over 5 Year
2481 TNX.Open_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2482 TNX.Open_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
2483 TNX.Open_SmoothDer Derivative of Smoothed
2485 TNX.Open_mva200 200 Day MA
2486 TNX.Open_mva050 50 Day MA
2489 TNX.High_YoY5 5 Year over 5 Year
2490 TNX.High_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2491 TNX.High_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
2492 TNX.High_SmoothDer Derivative of Smoothed
2494 TNX.High_mva200 200 Day MA
2495 TNX.High_mva050 50 Day MA
2498 TNX.Low_YoY5 5 Year over 5 Year
2499 TNX.Low_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2500 TNX.Low_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
2501 TNX.Low_SmoothDer Derivative of Smoothed
2503 TNX.Low_mva200 200 Day MA
2504 TNX.Low_mva050 50 Day MA
2508 TNX.Close_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2509 TNX.Close_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
2510 TNX.Close_SmoothDer Derivative of Smoothed
2512 TNX.Close_mva200 200 Day MA
2513 TNX.Close_mva050 50 Day MA
2514 TNX.Volume_YoY Year over Year
2515 TNX.Volume_YoY4 4 Year over 4 Year
2516 TNX.Volume_YoY5 5 Year over 5 Year
2517 TNX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2518 TNX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
2519 TNX.Volume_SmoothDer Derivative of Smoothed
2520 TNX.Volume_Log Log of
2521 TNX.Volume_mva200 200 Day MA
2522 TNX.Volume_mva050 50 Day MA
2526 TNX.Adjusted_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2527 TNX.Adjusted_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
2528 TNX.Adjusted_SmoothDer Derivative of Smoothed
2530 TNX.Adjusted_mva200 200 Day MA
2531 TNX.Adjusted_mva050 50 Day MA
2535 CLF.Open_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2537 CLF.Open_SmoothDer Derivative of Smoothed
2538 CLF.Open_Log Log of
2539 CLF.Open_mva200 200 Day MA
2540 CLF.Open_mva050 50 Day MA
2544 CLF.High_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2546 CLF.High_SmoothDer Derivative of Smoothed
2548 CLF.High_mva200 200 Day MA
2549 CLF.High_mva050 50 Day MA
2553 CLF.Low_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2555 CLF.Low_SmoothDer Derivative of Smoothed
2556 CLF.Low_Log Log of
2557 CLF.Low_mva200 200 Day MA
2558 CLF.Low_mva050 50 Day MA
2562 CLF.Close_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2564 CLF.Close_SmoothDer Derivative of Smoothed
2565 CLF.Close_Log Log of
2566 CLF.Close_mva200 200 Day MA
2567 CLF.Close_mva050 50 Day MA
2573 CLF.Volume_SmoothDer Derivative of Smoothed
2574 CLF.Volume_Log Log of
2580 CLF.Adjusted_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2582 CLF.Adjusted_SmoothDer Derivative of Smoothed
2583 CLF.Adjusted_Log Log of
2584 CLF.Adjusted_mva200 200 Day MA
2585 CLF.Adjusted_mva050 50 Day MA
2589 DGS30_Smooth Savitsky-Golay Smoothed (p=3, n=365) 10-Year Treasury Constant Maturity Rate
2591 DGS30_SmoothDer Derivative of Smoothed 10-Year Treasury Constant Maturity Rate
2594 DGS30_mva050 10-Year Treasury Constant Maturity Rate 50 Day MA
2598 DGS1_Smooth Savitsky-Golay Smoothed (p=3, n=365) 1-Year Treasury Constant Maturity Rate
2599 DGS1_Smooth.short Savitsky-Golay Smoothed (p=3, n=15) 1-Year Treasury Constant Maturity Rate
2600 DGS1_SmoothDer Derivative of Smoothed 1-Year Treasury Constant Maturity Rate
2602 DGS1_mva200 1-Year Treasury Constant Maturity Rate 200 Day MA
2603 DGS1_mva050 1-Year Treasury Constant Maturity Rate 50 Day MA
2604 DGS2_YoY 2-Year Treasury Constant Maturity Rate Year over Year
2607 DGS2_Smooth Savitsky-Golay Smoothed (p=3, n=365) 2-Year Treasury Constant Maturity Rate
2609 DGS2_SmoothDer Derivative of Smoothed 2-Year Treasury Constant Maturity Rate
2611 DGS2_mva200 2-Year Treasury Constant Maturity Rate 200 Day MA
2612 DGS2_mva050 2-Year Treasury Constant Maturity Rate 50 Day MA
2613 TB3MS_YoY 3-Month Treasury Bill: Secondary Market Rate (Monthly) Year over Year
2616 TB3MS_Smooth Savitsky-Golay Smoothed (p=3, n=365) 3-Month Treasury Bill: Secondary Market Rate (Monthly)
2618 TB3MS_SmoothDer Derivative of Smoothed 3-Month Treasury Bill: Secondary Market Rate (Monthly)
2619 TB3MS_Log Log of 3-Month Treasury Bill: Secondary Market Rate (Monthly)
2620 TB3MS_mva200 3-Month Treasury Bill: Secondary Market Rate (Monthly) 200 Day MA
2621 TB3MS_mva050 3-Month Treasury Bill: Secondary Market Rate (Monthly) 50 Day MA
2625 DTB3_Smooth Savitsky-Golay Smoothed (p=3, n=365) 3-Month Treasury Bill: Secondary Market Rate (Daily)
2627 DTB3_SmoothDer Derivative of Smoothed 3-Month Treasury Bill: Secondary Market Rate (Daily)
2628 DTB3_Log Log of 3-Month Treasury Bill: Secondary Market Rate (Daily)
2629 DTB3_mva200 3-Month Treasury Bill: Secondary Market Rate (Daily) 200 Day MA
2630 DTB3_mva050 3-Month Treasury Bill: Secondary Market Rate (Daily) 50 Day MA
2634 IRX.Open_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2635 IRX.Open_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
2636 IRX.Open_SmoothDer Derivative of Smoothed
2637 IRX.Open_Log Log of
2639 IRX.Open_mva050 50 Day MA
2643 IRX.High_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2644 IRX.High_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
2645 IRX.High_SmoothDer Derivative of Smoothed
2646 IRX.High_Log Log of
2648 IRX.High_mva050 50 Day MA
2652 IRX.Low_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2653 IRX.Low_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
2654 IRX.Low_SmoothDer Derivative of Smoothed
2655 IRX.Low_Log Log of
2656 IRX.Low_mva200 200 Day MA
2657 IRX.Low_mva050 50 Day MA
2661 IRX.Close_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2662 IRX.Close_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
2663 IRX.Close_SmoothDer Derivative of Smoothed
2664 IRX.Close_Log Log of
2665 IRX.Close_mva200 200 Day MA
2666 IRX.Close_mva050 50 Day MA
2667 IRX.Volume_YoY Year over Year
2668 IRX.Volume_YoY4 4 Year over 4 Year
2669 IRX.Volume_YoY5 5 Year over 5 Year
2670 IRX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2671 IRX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
2672 IRX.Volume_SmoothDer Derivative of Smoothed
2673 IRX.Volume_Log Log of
2674 IRX.Volume_mva200 200 Day MA
2675 IRX.Volume_mva050 50 Day MA
2679 IRX.Adjusted_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2680 IRX.Adjusted_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
2681 IRX.Adjusted_SmoothDer Derivative of Smoothed
2682 IRX.Adjusted_Log Log of
2683 IRX.Adjusted_mva200 200 Day MA
2684 IRX.Adjusted_mva050 50 Day MA
2688 DCOILWTICO_Smooth Savitsky-Golay Smoothed (p=3, n=365) Crude Oil Prices: West Texas Intermediate (WTI) Cushing, Oklahoma
2690 DCOILWTICO_SmoothDer Derivative of Smoothed Crude Oil Prices: West Texas Intermediate (WTI) Cushing, Oklahoma
2691 DCOILWTICO_Log Log of Crude Oil Prices: West Texas Intermediate (WTI) Cushing, Oklahoma
2692 DCOILWTICO_mva200 Crude Oil Prices: West Texas Intermediate (WTI) Cushing, Oklahoma 200 Day MA
2693 DCOILWTICO_mva050 Crude Oil Prices: West Texas Intermediate (WTI) Cushing, Oklahoma 50 Day MA
2697 DCOILBRENTEU_Smooth Savitsky-Golay Smoothed (p=3, n=365) Crude Oil Prices: Brent - Europe
2699 DCOILBRENTEU_SmoothDer Derivative of Smoothed Crude Oil Prices: Brent - Europe
2701 DCOILBRENTEU_mva200 Crude Oil Prices: Brent - Europe 200 Day MA
2702 DCOILBRENTEU_mva050 Crude Oil Prices: Brent - Europe 50 Day MA
2710 NEWORDER_mva200 Manufacturers’ New Orders: Nondefense Capital Goods Excluding Aircraft 200 Day MA
2715 ALTSALES_Smooth Savitsky-Golay Smoothed (p=3, n=365) Light Weight Vehicle Sales: Autos and Light Trucks
2717 ALTSALES_SmoothDer Derivative of Smoothed Light Weight Vehicle Sales: Autos and Light Trucks
2726 ICSA_SmoothDer Derivative of Smoothed Initial Jobless Claims
2769 GSPC.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2771 GSPC.Volume_SmoothDer Derivative of Smoothed
2820 RLG.Volume_YoY Year over Year
2821 RLG.Volume_YoY4 4 Year over 4 Year
2822 RLG.Volume_YoY5 5 Year over 5 Year
2823 RLG.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2824 RLG.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
2825 RLG.Volume_SmoothDer Derivative of Smoothed
2826 RLG.Volume_Log Log of
2827 RLG.Volume_mva200 200 Day MA
2828 RLG.Volume_mva050 50 Day MA
2877 DJI.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2879 DJI.Volume_SmoothDer Derivative of Smoothed
2881 DJI.Volume_mva200 200 Day MA
2931 STOXX50E.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2933 STOXX50E.Volume_SmoothDer Derivative of Smoothed
2934 STOXX50E.Volume_Log Log of
2935 STOXX50E.Volume_mva200 200 Day MA
2985 EFA.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2987 EFA.Volume_SmoothDer Derivative of Smoothed
2989 EFA.Volume_mva200 200 Day MA
3006 GDP_Log Log of Gross Domestic Product
3007 GDP_mva200 Gross Domestic Product 200 Day MA
3008 GDP_mva050 Gross Domestic Product 50 Day MA
3011 FNDEFX_YoY5 Federal Government: Nondefense Consumption Expenditures and Gross Investment (SA, Annual Rate) 5 Year over 5 Year
3014 FNDEFX_SmoothDer Derivative of Smoothed Federal Government: Nondefense Consumption Expenditures and Gross Investment (SA, Annual Rate)
3015 FNDEFX_Log Log of Federal Government: Nondefense Consumption Expenditures and Gross Investment (SA, Annual Rate)
3016 FNDEFX_mva200 Federal Government: Nondefense Consumption Expenditures and Gross Investment (SA, Annual Rate) 200 Day MA
3017 FNDEFX_mva050 Federal Government: Nondefense Consumption Expenditures and Gross Investment (SA, Annual Rate) 50 Day MA
3021 FDEFX_Smooth Savitsky-Golay Smoothed (p=3, n=365) Federal Government: National Defense Consumption Expenditures and Gross Investment (SA, Annual Rate)
3033 GDPNOW_Log Log of Fed Atlanta GDPNow
3042 GDPC1_Log Log of Real Gross Domestic Product
3043 GDPC1_mva200 Real Gross Domestic Product 200 Day MA
3044 GDPC1_mva050 Real Gross Domestic Product 50 Day MA
3051 GDPDEF_Log Log of Gross Domestic Product: Implicit Price Deflator
3052 GDPDEF_mva200 Gross Domestic Product: Implicit Price Deflator 200 Day MA
3053 GDPDEF_mva050 Gross Domestic Product: Implicit Price Deflator 50 Day MA
3095 VIG.Volume_SmoothDer Derivative of Smoothed
3112 WLRRAL_Smooth.short Savitsky-Golay Smoothed (p=3, n=15) Liabilities and Capital: Liabilities: Reverse Repurchase Agreements: Wednesday Level (NSA)
3114 WLRRAL_Log Log of Liabilities and Capital: Liabilities: Reverse Repurchase Agreements: Wednesday Level (NSA)
3115 WLRRAL_mva200 Liabilities and Capital: Liabilities: Reverse Repurchase Agreements: Wednesday Level (NSA) 200 Day MA
3117 FEDFUNDS_YoY Effective Federal Funds Rate Year over Year
3123 FEDFUNDS_Log Log of Effective Federal Funds Rate
3132 GPDI_Log Log of Gross Private Domestic Investment
3133 GPDI_mva200 Gross Private Domestic Investment 200 Day MA
3134 GPDI_mva050 Gross Private Domestic Investment 50 Day MA
3135 W790RC1Q027SBEA_YoY Net domestic investment: Private: Domestic busines Year over Year
3141 W790RC1Q027SBEA_Log Log of Net domestic investment: Private: Domestic busines
3142 W790RC1Q027SBEA_mva200 Net domestic investment: Private: Domestic busines 200 Day MA
3143 W790RC1Q027SBEA_mva050 Net domestic investment: Private: Domestic busines 50 Day MA
3144 MZMV_YoY Velocity of MZM Money Stock Year over Year
3146 MZMV_YoY5 Velocity of MZM Money Stock 5 Year over 5 Year
3150 MZMV_Log Log of Velocity of MZM Money Stock
3151 MZMV_mva200 Velocity of MZM Money Stock 200 Day MA
3152 MZMV_mva050 Velocity of MZM Money Stock 50 Day MA
3158 M1_SmoothDer Derivative of Smoothed M1 Money Stock
3159 M1_Log Log of M1 Money Stock
3160 M1_mva200 M1 Money Stock 200 Day MA
3161 M1_mva050 M1 Money Stock 50 Day MA
3167 M2_SmoothDer Derivative of Smoothed M2 Money Stock
3168 M2_Log Log of M2 Money Stock
3169 M2_mva200 M2 Money Stock 200 Day MA
3170 M2_mva050 M2 Money Stock 50 Day MA
3173 OPHNFB_YoY5 Nonfarm Business Sector: Real Output Per Hour of All Persons 5 Year over 5 Year
3177 OPHNFB_Log Log of Nonfarm Business Sector: Real Output Per Hour of All Persons
3178 OPHNFB_mva200 Nonfarm Business Sector: Real Output Per Hour of All Persons 200 Day MA
3179 OPHNFB_mva050 Nonfarm Business Sector: Real Output Per Hour of All Persons 50 Day MA
3183 IPMAN_Smooth Savitsky-Golay Smoothed (p=3, n=365) Industrial Production: Manufacturing (NAICS)
3186 IPMAN_Log Log of Industrial Production: Manufacturing (NAICS)
3187 IPMAN_mva200 Industrial Production: Manufacturing (NAICS) 200 Day MA
3188 IPMAN_mva050 Industrial Production: Manufacturing (NAICS) 50 Day MA
3230 IWD.Volume_SmoothDer Derivative of Smoothed
3241 IWD.Adjusted_mva200 200 Day MA
3245 GS5_YoY5 5-Year Treasury Constant Maturity Rate 5 Year over 5 Year
3246 GS5_Smooth Savitsky-Golay Smoothed (p=3, n=365) 5-Year Treasury Constant Maturity Rate
3248 GS5_SmoothDer Derivative of Smoothed 5-Year Treasury Constant Maturity Rate
3249 GS5_Log Log of 5-Year Treasury Constant Maturity Rate
3250 GS5_mva200 5-Year Treasury Constant Maturity Rate 200 Day MA
3251 GS5_mva050 5-Year Treasury Constant Maturity Rate 50 Day MA
3257 PSAVERT_SmoothDer Derivative of Smoothed Personal Saving Rate
3264 VIXCLS_Smooth Savitsky-Golay Smoothed (p=3, n=365) CBOE Volatility Index
3266 VIXCLS_SmoothDer Derivative of Smoothed CBOE Volatility Index
3268 VIXCLS_mva200 CBOE Volatility Index 200 Day MA
3273 VXX.Open_Smooth Savitsky-Golay Smoothed (p=3, n=365)
3275 VXX.Open_SmoothDer Derivative of Smoothed
3282 VXX.High_Smooth Savitsky-Golay Smoothed (p=3, n=365)
3284 VXX.High_SmoothDer Derivative of Smoothed
3291 VXX.Low_Smooth Savitsky-Golay Smoothed (p=3, n=365)
3293 VXX.Low_SmoothDer Derivative of Smoothed
3300 VXX.Close_Smooth Savitsky-Golay Smoothed (p=3, n=365)
3302 VXX.Close_SmoothDer Derivative of Smoothed
3308 VXX.Volume_YoY5 5 Year over 5 Year
3312 VXX.Volume_Log Log of
3318 VXX.Adjusted_Smooth Savitsky-Golay Smoothed (p=3, n=365)
3320 VXX.Adjusted_SmoothDer Derivative of Smoothed
3327 HOUST1F_Smooth Savitsky-Golay Smoothed (p=3, n=365) Privately Owned Housing Starts: 1-Unit Structures
3331 HOUST1F_mva200 Privately Owned Housing Starts: 1-Unit Structures 200 Day MA
3332 HOUST1F_mva050 Privately Owned Housing Starts: 1-Unit Structures 50 Day MA
3335 GFDEBTN_YoY5 Federal Debt: Total Public Debt 5 Year over 5 Year
3339 GFDEBTN_Log Log of Federal Debt: Total Public Debt
3340 GFDEBTN_mva200 Federal Debt: Total Public Debt 200 Day MA
3341 GFDEBTN_mva050 Federal Debt: Total Public Debt 50 Day MA
3344 HOUST_YoY5 Housing Starts: Total: New Privately Owned Housing Units Started 5 Year over 5 Year
3345 HOUST_Smooth Savitsky-Golay Smoothed (p=3, n=365) Housing Starts: Total: New Privately Owned Housing Units Started
3347 HOUST_SmoothDer Derivative of Smoothed Housing Starts: Total: New Privately Owned Housing Units Started
3348 HOUST_Log Log of Housing Starts: Total: New Privately Owned Housing Units Started
3349 HOUST_mva200 Housing Starts: Total: New Privately Owned Housing Units Started 200 Day MA
3350 HOUST_mva050 Housing Starts: Total: New Privately Owned Housing Units Started 50 Day MA
3352 MSPUS_YoY4 Median Sales Price of Houses Sold for the United States 4 Year over 4 Year
3354 MSPUS_Smooth Savitsky-Golay Smoothed (p=3, n=365) Median Sales Price of Houses Sold for the United States
3376 DGORDER_mva200 Manufacturers’ New Orders: Durable Goods (SA) 200 Day MA
3384 CSUSHPINSA_Log Log of S&P/Case-Shiller U.S. National Home Price Index (NSA)
3385 CSUSHPINSA_mva200 S&P/Case-Shiller U.S. National Home Price Index (NSA) 200 Day MA
3386 CSUSHPINSA_mva050 S&P/Case-Shiller U.S. National Home Price Index (NSA) 50 Day MA
3387 GFDEGDQ188S_YoY Federal Debt: Total Public Debt as Percent of Gross Domestic Product Year over Year
3389 GFDEGDQ188S_YoY5 Federal Debt: Total Public Debt as Percent of Gross Domestic Product 5 Year over 5 Year
3392 GFDEGDQ188S_SmoothDer Derivative of Smoothed Federal Debt: Total Public Debt as Percent of Gross Domestic Product
3393 GFDEGDQ188S_Log Log of Federal Debt: Total Public Debt as Percent of Gross Domestic Product
3395 GFDEGDQ188S_mva050 Federal Debt: Total Public Debt as Percent of Gross Domestic Product 50 Day MA
3396 FYFSD_YoY Federal Surplus or Deficit Year over Year
3402 FYFSD_Log Log of Federal Surplus or Deficit
3403 FYFSD_mva200 Federal Surplus or Deficit 200 Day MA
3404 FYFSD_mva050 Federal Surplus or Deficit 50 Day MA
3405 FYFSGDA188S_YoY Federal Surplus or Deficit [-] as Percent of Gross Domestic Product Year over Year
3410 FYFSGDA188S_SmoothDer Derivative of Smoothed Federal Surplus or Deficit [-] as Percent of Gross Domestic Product
3411 FYFSGDA188S_Log Log of Federal Surplus or Deficit [-] as Percent of Gross Domestic Product
3412 FYFSGDA188S_mva200 Federal Surplus or Deficit [-] as Percent of Gross Domestic Product 200 Day MA
3413 FYFSGDA188S_mva050 Federal Surplus or Deficit [-] as Percent of Gross Domestic Product 50 Day MA
3417 GDX.Open_Smooth Savitsky-Golay Smoothed (p=3, n=365)
3418 GDX.Open_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
3419 GDX.Open_SmoothDer Derivative of Smoothed
3420 GDX.Open_Log Log of
3422 GDX.Open_mva050 50 Day MA
3426 GDX.High_Smooth Savitsky-Golay Smoothed (p=3, n=365)
3427 GDX.High_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
3428 GDX.High_SmoothDer Derivative of Smoothed
3431 GDX.High_mva050 50 Day MA
3435 GDX.Low_Smooth Savitsky-Golay Smoothed (p=3, n=365)
3436 GDX.Low_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
3437 GDX.Low_SmoothDer Derivative of Smoothed
3438 GDX.Low_Log Log of
3440 GDX.Low_mva050 50 Day MA
3444 GDX.Close_Smooth Savitsky-Golay Smoothed (p=3, n=365)
3446 GDX.Close_SmoothDer Derivative of Smoothed
3449 GDX.Close_mva050 50 Day MA
3453 GDX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
3455 GDX.Volume_SmoothDer Derivative of Smoothed
3462 GDX.Adjusted_Smooth Savitsky-Golay Smoothed (p=3, n=365)
3464 GDX.Adjusted_SmoothDer Derivative of Smoothed
3467 GDX.Adjusted_mva050 50 Day MA
3470 XLE.Open_YoY5 5 Year over 5 Year
3471 XLE.Open_Smooth Savitsky-Golay Smoothed (p=3, n=365)
3472 XLE.Open_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
3473 XLE.Open_SmoothDer Derivative of Smoothed
3475 XLE.Open_mva200 200 Day MA
3476 XLE.Open_mva050 50 Day MA
3480 XLE.High_Smooth Savitsky-Golay Smoothed (p=3, n=365)
3482 XLE.High_SmoothDer Derivative of Smoothed
3484 XLE.High_mva200 200 Day MA
3485 XLE.High_mva050 50 Day MA
3488 XLE.Low_YoY5 5 Year over 5 Year
3489 XLE.Low_Smooth Savitsky-Golay Smoothed (p=3, n=365)
3490 XLE.Low_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
3491 XLE.Low_SmoothDer Derivative of Smoothed
3493 XLE.Low_mva200 200 Day MA
3494 XLE.Low_mva050 50 Day MA
3497 XLE.Close_YoY5 5 Year over 5 Year
3498 XLE.Close_Smooth Savitsky-Golay Smoothed (p=3, n=365)
3500 XLE.Close_SmoothDer Derivative of Smoothed
3502 XLE.Close_mva200 200 Day MA
3503 XLE.Close_mva050 50 Day MA
3507 XLE.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
3509 XLE.Volume_SmoothDer Derivative of Smoothed
3511 XLE.Volume_mva200 200 Day MA
3515 XLE.Adjusted_YoY5 5 Year over 5 Year
3516 XLE.Adjusted_Smooth Savitsky-Golay Smoothed (p=3, n=365)
3517 XLE.Adjusted_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
3518 XLE.Adjusted_SmoothDer Derivative of Smoothed
3519 XLE.Adjusted_Log Log of
3520 XLE.Adjusted_mva200 200 Day MA
3521 XLE.Adjusted_mva050 50 Day MA
3522 GSG.Open_YoY Year over Year
3525 GSG.Open_Smooth Savitsky-Golay Smoothed (p=3, n=365)
3526 GSG.Open_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
3527 GSG.Open_SmoothDer Derivative of Smoothed
3529 GSG.Open_mva200 200 Day MA
3530 GSG.Open_mva050 50 Day MA
3534 GSG.High_Smooth Savitsky-Golay Smoothed (p=3, n=365)
3536 GSG.High_SmoothDer Derivative of Smoothed
3538 GSG.High_mva200 200 Day MA
3539 GSG.High_mva050 50 Day MA
3543 GSG.Low_Smooth Savitsky-Golay Smoothed (p=3, n=365)
3544 GSG.Low_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
3545 GSG.Low_SmoothDer Derivative of Smoothed
3547 GSG.Low_mva200 200 Day MA
3548 GSG.Low_mva050 50 Day MA
3552 GSG.Close_Smooth Savitsky-Golay Smoothed (p=3, n=365)
3554 GSG.Close_SmoothDer Derivative of Smoothed
3556 GSG.Close_mva200 200 Day MA
3557 GSG.Close_mva050 50 Day MA
3561 GSG.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
3563 GSG.Volume_SmoothDer Derivative of Smoothed
3565 GSG.Volume_mva200 200 Day MA
3570 GSG.Adjusted_Smooth Savitsky-Golay Smoothed (p=3, n=365)
3572 GSG.Adjusted_SmoothDer Derivative of Smoothed
3574 GSG.Adjusted_mva200 200 Day MA
3575 GSG.Adjusted_mva050 50 Day MA
3577 WALCL_YoY4 All Federal Reserve Banks: Total Assets 4 Year over 4 Year
3578 WALCL_YoY5 All Federal Reserve Banks: Total Assets 5 Year over 5 Year
3579 WALCL_Smooth Savitsky-Golay Smoothed (p=3, n=365) All Federal Reserve Banks: Total Assets
3580 WALCL_Smooth.short Savitsky-Golay Smoothed (p=3, n=15) All Federal Reserve Banks: Total Assets
3582 WALCL_Log Log of All Federal Reserve Banks: Total Assets
3583 WALCL_mva200 All Federal Reserve Banks: Total Assets 200 Day MA
3584 WALCL_mva050 All Federal Reserve Banks: Total Assets 50 Day MA
3591 OUTMS_Log Log of Manufacturing Sector: Real Output
3592 OUTMS_mva200 Manufacturing Sector: Real Output 200 Day MA
3593 OUTMS_mva050 Manufacturing Sector: Real Output 50 Day MA
3600 MANEMP_Log Log of All Employees: Manufacturing
3601 MANEMP_mva200 All Employees: Manufacturing 200 Day MA
3602 MANEMP_mva050 All Employees: Manufacturing 50 Day MA
3608 PRS30006163_SmoothDer Derivative of Smoothed Manufacturing Sector: Real Output Per Person
3615 BAMLC0A3CA_Smooth Savitsky-Golay Smoothed (p=3, n=365) ICE BofAML US Corporate A Option-Adjusted Spread
3617 BAMLC0A3CA_SmoothDer Derivative of Smoothed ICE BofAML US Corporate A Option-Adjusted Spread
3619 BAMLC0A3CA_mva200 ICE BofAML US Corporate A Option-Adjusted Spread 200 Day MA
3620 BAMLC0A3CA_mva050 ICE BofAML US Corporate A Option-Adjusted Spread 50 Day MA
3623 AAA_YoY5 Moody’s Seasoned Aaa Corporate Bond Yield 5 Year over 5 Year
3624 AAA_Smooth Savitsky-Golay Smoothed (p=3, n=365) Moody’s Seasoned Aaa Corporate Bond Yield
3626 AAA_SmoothDer Derivative of Smoothed Moody’s Seasoned Aaa Corporate Bond Yield
3627 AAA_Log Log of Moody’s Seasoned Aaa Corporate Bond Yield
3628 AAA_mva200 Moody’s Seasoned Aaa Corporate Bond Yield 200 Day MA
3629 AAA_mva050 Moody’s Seasoned Aaa Corporate Bond Yield 50 Day MA
3633 SOFR_Smooth Savitsky-Golay Smoothed (p=3, n=365) Secured Overnight Financing Rate
3635 SOFR_SmoothDer Derivative of Smoothed Secured Overnight Financing Rate
3637 SOFR_mva200 Secured Overnight Financing Rate 200 Day MA
3638 SOFR_mva050 Secured Overnight Financing Rate 50 Day MA
3642 SOFRVOL_Smooth Savitsky-Golay Smoothed (p=3, n=365) Secured Overnight Financing Volume
3644 SOFRVOL_SmoothDer Derivative of Smoothed Secured Overnight Financing Volume
3648 SOFR99_YoY Secured Overnight Financing Rate: 99th Percentile Year over Year
3649 SOFR99_YoY4 Secured Overnight Financing Rate: 99th Percentile 4 Year over 4 Year
3650 SOFR99_YoY5 Secured Overnight Financing Rate: 99th Percentile 5 Year over 5 Year
3651 SOFR99_Smooth Savitsky-Golay Smoothed (p=3, n=365) Secured Overnight Financing Rate: 99th Percentile
3653 SOFR99_SmoothDer Derivative of Smoothed Secured Overnight Financing Rate: 99th Percentile
3654 SOFR99_Log Log of Secured Overnight Financing Rate: 99th Percentile
3655 SOFR99_mva200 Secured Overnight Financing Rate: 99th Percentile 200 Day MA
3656 SOFR99_mva050 Secured Overnight Financing Rate: 99th Percentile 50 Day MA
3658 SOFR75_YoY4 Secured Overnight Financing Rate: 75th Percentile 4 Year over 4 Year
3659 SOFR75_YoY5 Secured Overnight Financing Rate: 75th Percentile 5 Year over 5 Year
3660 SOFR75_Smooth Savitsky-Golay Smoothed (p=3, n=365) Secured Overnight Financing Rate: 75th Percentile
3662 SOFR75_SmoothDer Derivative of Smoothed Secured Overnight Financing Rate: 75th Percentile
3663 SOFR75_Log Log of Secured Overnight Financing Rate: 75th Percentile
3664 SOFR75_mva200 Secured Overnight Financing Rate: 75th Percentile 200 Day MA
3665 SOFR75_mva050 Secured Overnight Financing Rate: 75th Percentile 50 Day MA
3669 SOFR25_Smooth Savitsky-Golay Smoothed (p=3, n=365) Secured Overnight Financing Rate: 25th Percentile
3671 SOFR25_SmoothDer Derivative of Smoothed Secured Overnight Financing Rate: 25th Percentile
3672 SOFR25_Log Log of Secured Overnight Financing Rate: 25th Percentile
3673 SOFR25_mva200 Secured Overnight Financing Rate: 25th Percentile 200 Day MA
3674 SOFR25_mva050 Secured Overnight Financing Rate: 25th Percentile 50 Day MA
3675 SOFR1_YoY Secured Overnight Financing Rate: 1st Percentile Year over Year
3678 SOFR1_Smooth Savitsky-Golay Smoothed (p=3, n=365) Secured Overnight Financing Rate: 1st Percentile
3680 SOFR1_SmoothDer Derivative of Smoothed Secured Overnight Financing Rate: 1st Percentile
3681 SOFR1_Log Log of Secured Overnight Financing Rate: 1st Percentile
3682 SOFR1_mva200 Secured Overnight Financing Rate: 1st Percentile 200 Day MA
3683 SOFR1_mva050 Secured Overnight Financing Rate: 1st Percentile 50 Day MA
3684 OBFR_YoY Overnight Bank Funding Rate Year over Year
3686 OBFR_YoY5 Overnight Bank Funding Rate 5 Year over 5 Year
3687 OBFR_Smooth Savitsky-Golay Smoothed (p=3, n=365) Overnight Bank Funding Rate
3689 OBFR_SmoothDer Derivative of Smoothed Overnight Bank Funding Rate
3690 OBFR_Log Log of Overnight Bank Funding Rate
3691 OBFR_mva200 Overnight Bank Funding Rate 200 Day MA
3692 OBFR_mva050 Overnight Bank Funding Rate 50 Day MA
3693 OBFR99_YoY Overnight Bank Funding Rate: 99th Percentile Year over Year
3695 OBFR99_YoY5 Overnight Bank Funding Rate: 99th Percentile 5 Year over 5 Year
3696 OBFR99_Smooth Savitsky-Golay Smoothed (p=3, n=365) Overnight Bank Funding Rate: 99th Percentile
3698 OBFR99_SmoothDer Derivative of Smoothed Overnight Bank Funding Rate: 99th Percentile
3699 OBFR99_Log Log of Overnight Bank Funding Rate: 99th Percentile
3700 OBFR99_mva200 Overnight Bank Funding Rate: 99th Percentile 200 Day MA
3701 OBFR99_mva050 Overnight Bank Funding Rate: 99th Percentile 50 Day MA
3702 OBFR75_YoY Overnight Bank Funding Rate: 75th Percentile Year over Year
3704 OBFR75_YoY5 Overnight Bank Funding Rate: 75th Percentile 5 Year over 5 Year
3705 OBFR75_Smooth Savitsky-Golay Smoothed (p=3, n=365) Overnight Bank Funding Rate: 75th Percentile
3707 OBFR75_SmoothDer Derivative of Smoothed Overnight Bank Funding Rate: 75th Percentile
3708 OBFR75_Log Log of Overnight Bank Funding Rate: 75th Percentile
3709 OBFR75_mva200 Overnight Bank Funding Rate: 75th Percentile 200 Day MA
3710 OBFR75_mva050 Overnight Bank Funding Rate: 75th Percentile 50 Day MA
3711 OBFR25_YoY Overnight Bank Funding Rate: 25th Percentile Year over Year
3713 OBFR25_YoY5 Overnight Bank Funding Rate: 25th Percentile 5 Year over 5 Year
3714 OBFR25_Smooth Savitsky-Golay Smoothed (p=3, n=365) Overnight Bank Funding Rate: 25th Percentile
3716 OBFR25_SmoothDer Derivative of Smoothed Overnight Bank Funding Rate: 25th Percentile
3717 OBFR25_Log Log of Overnight Bank Funding Rate: 25th Percentile
3718 OBFR25_mva200 Overnight Bank Funding Rate: 25th Percentile 200 Day MA
3719 OBFR25_mva050 Overnight Bank Funding Rate: 25th Percentile 50 Day MA
3723 OBFR1_Smooth Savitsky-Golay Smoothed (p=3, n=365) Overnight Bank Funding Rate: 1st Percentile
3725 OBFR1_SmoothDer Derivative of Smoothed Overnight Bank Funding Rate: 1st Percentile
3727 OBFR1_mva200 Overnight Bank Funding Rate: 1st Percentile 200 Day MA
3728 OBFR1_mva050 Overnight Bank Funding Rate: 1st Percentile 50 Day MA
3735 RPONTSYD_Log Log of Overnight Repurchase Agreements: Treasury Securities Purchased by the Federal Reserve in the Temporary Open Market Operations
3738 IOER_YoY Interest Rate on Excess Reserves Year over Year
3744 IOER_Log Log of Interest Rate on Excess Reserves
3745 IOER_mva200 Interest Rate on Excess Reserves 200 Day MA
3746 IOER_mva050 Interest Rate on Excess Reserves 50 Day MA
3756 EXCSRESNW_YoY Excess Reserves of Depository Institutions Year over Year
3762 EXCSRESNW_Log Log of Excess Reserves of Depository Institutions
3763 EXCSRESNW_mva200 Excess Reserves of Depository Institutions 200 Day MA
3764 EXCSRESNW_mva050 Excess Reserves of Depository Institutions 50 Day MA
3765 ECBASSETS_YoY Central Bank Assets for Euro Area (11-19 Countries) Year over Year
3771 ECBASSETS_Log Log of Central Bank Assets for Euro Area (11-19 Countries)
3772 ECBASSETS_mva200 Central Bank Assets for Euro Area (11-19 Countries) 200 Day MA
3773 ECBASSETS_mva050 Central Bank Assets for Euro Area (11-19 Countries) 50 Day MA
3780 EUNNGDP_Log Log of Gross Domestic Product (Euro/ECU series) for Euro Area (19 Countries)
3781 EUNNGDP_mva200 Gross Domestic Product (Euro/ECU series) for Euro Area (19 Countries) 200 Day MA
3782 EUNNGDP_mva050 Gross Domestic Product (Euro/ECU series) for Euro Area (19 Countries) 50 Day MA
3785 CEU0600000007_YoY5 Average Weekly Hours of Production and Nonsupervisory Employees: Goods-Producing 5 Year over 5 Year
3797 CURRENCY_SmoothDer Derivative of Smoothed Currency Component of M1 (Seasonally Adjusted)
3798 CURRENCY_Log Log of Currency Component of M1 (Seasonally Adjusted)
3799 CURRENCY_mva200 Currency Component of M1 (Seasonally Adjusted) 200 Day MA
3800 CURRENCY_mva050 Currency Component of M1 (Seasonally Adjusted) 50 Day MA
3804 WCURRNS_Smooth Savitsky-Golay Smoothed (p=3, n=365) Currency Component of M1
3807 WCURRNS_Log Log of Currency Component of M1
3808 WCURRNS_mva200 Currency Component of M1 200 Day MA
3809 WCURRNS_mva050 Currency Component of M1 50 Day MA
3822 PRS88003193_Smooth Savitsky-Golay Smoothed (p=3, n=365) Nonfinancial Corporations Sector: Unit Profits
3824 PRS88003193_SmoothDer Derivative of Smoothed Nonfinancial Corporations Sector: Unit Profits
3825 PRS88003193_Log Log of Nonfinancial Corporations Sector: Unit Profits
3826 PRS88003193_mva200 Nonfinancial Corporations Sector: Unit Profits 200 Day MA
3827 PRS88003193_mva050 Nonfinancial Corporations Sector: Unit Profits 50 Day MA
3831 PPIACO_Smooth Savitsky-Golay Smoothed (p=3, n=365) Producer Price Index for All Commodities
3833 PPIACO_SmoothDer Derivative of Smoothed Producer Price Index for All Commodities
3834 PPIACO_Log Log of Producer Price Index for All Commodities
3835 PPIACO_mva200 Producer Price Index for All Commodities 200 Day MA
3836 PPIACO_mva050 Producer Price Index for All Commodities 50 Day MA
3840 PCUOMFGOMFG_Smooth Savitsky-Golay Smoothed (p=3, n=365) Producer Price Index by Industry: Total Manufacturing Industries
3842 PCUOMFGOMFG_SmoothDer Derivative of Smoothed Producer Price Index by Industry: Total Manufacturing Industries
3843 PCUOMFGOMFG_Log Log of Producer Price Index by Industry: Total Manufacturing Industries
3844 PCUOMFGOMFG_mva200 Producer Price Index by Industry: Total Manufacturing Industries 200 Day MA
3845 PCUOMFGOMFG_mva050 Producer Price Index by Industry: Total Manufacturing Industries 50 Day MA
3858 POPTHM_Log Log of Population (U.S.)
3859 POPTHM_Log Log of Population (U.S.)
3860 POPTHM_mva200 Population (U.S.) 200 Day MA
3861 POPTHM_mva200 Population (U.S.) 200 Day MA
3862 POPTHM_mva050 Population (U.S.) 50 Day MA
3863 POPTHM_mva050 Population (U.S.) 50 Day MA
3876 POPTHM.1_Log Log of
3877 POPTHM.1_Log Log of
3878 POPTHM.1_mva200 200 Day MA
3879 POPTHM.1_mva200 200 Day MA
3880 POPTHM.1_mva050 50 Day MA
3881 POPTHM.1_mva050 50 Day MA
3885 CLF16OV_Smooth Savitsky-Golay Smoothed (p=3, n=365) Civilian Labor Force Level, SA
3887 CLF16OV_SmoothDer Derivative of Smoothed Civilian Labor Force Level, SA
3888 CLF16OV_Log Log of Civilian Labor Force Level, SA
3889 CLF16OV_mva200 Civilian Labor Force Level, SA 200 Day MA
3890 CLF16OV_mva050 Civilian Labor Force Level, SA 50 Day MA
3894 LNU01000000_Smooth Savitsky-Golay Smoothed (p=3, n=365) Civilian Labor Force Level, NSA
3896 LNU01000000_SmoothDer Derivative of Smoothed Civilian Labor Force Level, NSA
3897 LNU01000000_Log Log of Civilian Labor Force Level, NSA
3898 LNU01000000_mva200 Civilian Labor Force Level, NSA 200 Day MA
3899 LNU01000000_mva050 Civilian Labor Force Level, NSA 50 Day MA
3900 LNU03000000_YoY Unemployment Level (NSA) Year over Year
3901 LNU03000000_YoY4 Unemployment Level (NSA) 4 Year over 4 Year
3902 LNU03000000_YoY5 Unemployment Level (NSA) 5 Year over 5 Year
3903 LNU03000000_Smooth Savitsky-Golay Smoothed (p=3, n=365) Unemployment Level (NSA)
3905 LNU03000000_SmoothDer Derivative of Smoothed Unemployment Level (NSA)
3914 UNEMPLOY_SmoothDer Derivative of Smoothed Unemployment Level, seasonally adjusted
3921 RSAFS_Smooth Savitsky-Golay Smoothed (p=3, n=365) Advance Retail Sales: Retail and Food Services
3923 RSAFS_SmoothDer Derivative of Smoothed Advance Retail Sales: Retail and Food Services
3924 RSAFS_Log Log of Advance Retail Sales: Retail and Food Services
3925 RSAFS_mva200 Advance Retail Sales: Retail and Food Services 200 Day MA
3926 RSAFS_mva050 Advance Retail Sales: Retail and Food Services 50 Day MA
3932 FRGSHPUSM649NCIS_SmoothDer Derivative of Smoothed Cass Freight Index: Shipments
3937 BOPGTB_YoY4 Trade Balance: Goods, Balance of Payments Basis (SA) 4 Year over 4 Year
3942 BOPGTB_Log Log of Trade Balance: Goods, Balance of Payments Basis (SA)
3950 TERMCBPER24NS_SmoothDer Derivative of Smoothed Finance Rate on Personal Loans at Commercial Banks, 24 Month Loan
3959 A065RC1A027NBEA_SmoothDer Derivative of Smoothed Personal income (NSA)
3960 A065RC1A027NBEA_Log Log of Personal income (NSA)
3961 A065RC1A027NBEA_mva200 Personal income (NSA) 200 Day MA
3962 A065RC1A027NBEA_mva050 Personal income (NSA) 50 Day MA
3968 PI_SmoothDer Derivative of Smoothed Personal income (SA)
3969 PI_Log Log of Personal income (SA)
3970 PI_mva200 Personal income (SA) 200 Day MA
3971 PI_mva050 Personal income (SA) 50 Day MA
3978 PCE_Log Log of Personal Consumption Expenditures (SA)
3979 PCE_mva200 Personal Consumption Expenditures (SA) 200 Day MA
3980 PCE_mva050 Personal Consumption Expenditures (SA) 50 Day MA
3984 A053RC1Q027SBEA_Smooth Savitsky-Golay Smoothed (p=3, n=365) National income: Corporate profits before tax (without IVA and CCAdj)
3986 A053RC1Q027SBEA_SmoothDer Derivative of Smoothed National income: Corporate profits before tax (without IVA and CCAdj)
3987 A053RC1Q027SBEA_Log Log of National income: Corporate profits before tax (without IVA and CCAdj)
3988 A053RC1Q027SBEA_mva200 National income: Corporate profits before tax (without IVA and CCAdj) 200 Day MA
3989 A053RC1Q027SBEA_mva050 National income: Corporate profits before tax (without IVA and CCAdj) 50 Day MA
3993 CPROFIT_Smooth Savitsky-Golay Smoothed (p=3, n=365) Corporate Profits with Inventory Valuation Adjustment (IVA) and Capital Consumption Adjustment (CCAdj)
3996 CPROFIT_Log Log of Corporate Profits with Inventory Valuation Adjustment (IVA) and Capital Consumption Adjustment (CCAdj)
3997 CPROFIT_mva200 Corporate Profits with Inventory Valuation Adjustment (IVA) and Capital Consumption Adjustment (CCAdj) 200 Day MA
3998 CPROFIT_mva050 Corporate Profits with Inventory Valuation Adjustment (IVA) and Capital Consumption Adjustment (CCAdj) 50 Day MA
4038 SPY.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
4040 SPY.Volume_SmoothDer Derivative of Smoothed
4042 SPY.Volume_mva200 200 Day MA
4092 MDY.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
4094 MDY.Volume_SmoothDer Derivative of Smoothed
4146 EES.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
4148 EES.Volume_SmoothDer Derivative of Smoothed
4149 EES.Volume_Log Log of
4150 EES.Volume_mva200 200 Day MA
4157 EES.Adjusted_SmoothDer Derivative of Smoothed
4166 IJR.Open_SmoothDer Derivative of Smoothed
4175 IJR.High_SmoothDer Derivative of Smoothed
4184 IJR.Low_SmoothDer Derivative of Smoothed
4193 IJR.Close_SmoothDer Derivative of Smoothed
4200 IJR.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
4202 IJR.Volume_SmoothDer Derivative of Smoothed
4204 IJR.Volume_mva200 200 Day MA
4211 IJR.Adjusted_SmoothDer Derivative of Smoothed
4251 VGSTX.Volume_YoY Year over Year
4252 VGSTX.Volume_YoY4 4 Year over 4 Year
4253 VGSTX.Volume_YoY5 5 Year over 5 Year
4254 VGSTX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
4255 VGSTX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
4256 VGSTX.Volume_SmoothDer Derivative of Smoothed
4257 VGSTX.Volume_Log Log of
4258 VGSTX.Volume_mva200 200 Day MA
4259 VGSTX.Volume_mva050 50 Day MA
4305 VFINX.Volume_YoY Year over Year
4306 VFINX.Volume_YoY4 4 Year over 4 Year
4307 VFINX.Volume_YoY5 5 Year over 5 Year
4308 VFINX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
4309 VFINX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
4310 VFINX.Volume_SmoothDer Derivative of Smoothed
4311 VFINX.Volume_Log Log of
4312 VFINX.Volume_mva200 200 Day MA
4313 VFINX.Volume_mva050 50 Day MA
4330 VOE.Open_mva200 200 Day MA
4339 VOE.High_mva200 200 Day MA
4348 VOE.Low_mva200 200 Day MA
4357 VOE.Close_mva200 200 Day MA
4362 VOE.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
4364 VOE.Volume_SmoothDer Derivative of Smoothed
4366 VOE.Volume_mva200 200 Day MA
4375 VOE.Adjusted_mva200 200 Day MA
4416 VOT.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
4418 VOT.Volume_SmoothDer Derivative of Smoothed
4420 VOT.Volume_mva200 200 Day MA
4467 TMFGX.Volume_YoY Year over Year
4468 TMFGX.Volume_YoY4 4 Year over 4 Year
4469 TMFGX.Volume_YoY5 5 Year over 5 Year
4470 TMFGX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
4471 TMFGX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
4472 TMFGX.Volume_SmoothDer Derivative of Smoothed
4473 TMFGX.Volume_Log Log of
4474 TMFGX.Volume_mva200 200 Day MA
4475 TMFGX.Volume_mva050 50 Day MA
4526 IWM.Volume_SmoothDer Derivative of Smoothed
4528 IWM.Volume_mva200 200 Day MA
4578 ONEQ.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
4580 ONEQ.Volume_SmoothDer Derivative of Smoothed
4582 ONEQ.Volume_mva200 200 Day MA
4629 HAINX.Volume_YoY Year over Year
4630 HAINX.Volume_YoY4 4 Year over 4 Year
4631 HAINX.Volume_YoY5 5 Year over 5 Year
4632 HAINX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
4633 HAINX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
4634 HAINX.Volume_SmoothDer Derivative of Smoothed
4635 HAINX.Volume_Log Log of
4636 HAINX.Volume_mva200 200 Day MA
4637 HAINX.Volume_mva050 50 Day MA
4686 VEU.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
4688 VEU.Volume_SmoothDer Derivative of Smoothed
4690 VEU.Volume_mva200 200 Day MA
4706 BIL.Open_SmoothDer Derivative of Smoothed
4715 BIL.High_SmoothDer Derivative of Smoothed
4724 BIL.Low_SmoothDer Derivative of Smoothed
4733 BIL.Close_SmoothDer Derivative of Smoothed
4740 BIL.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
4742 BIL.Volume_SmoothDer Derivative of Smoothed
4744 BIL.Volume_mva200 200 Day MA
4751 BIL.Adjusted_SmoothDer Derivative of Smoothed
4796 IVOO.Volume_SmoothDer Derivative of Smoothed
4797 IVOO.Volume_Log Log of
4848 VO.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
4850 VO.Volume_SmoothDer Derivative of Smoothed
4851 VO.Volume_Log Log of
4902 CZA.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
4904 CZA.Volume_SmoothDer Derivative of Smoothed
4905 CZA.Volume_Log Log of
4906 CZA.Volume_mva200 200 Day MA
4918 VYM.Open_YoY4 4 Year over 4 Year
4920 VYM.Open_Smooth Savitsky-Golay Smoothed (p=3, n=365)
4922 VYM.Open_SmoothDer Derivative of Smoothed
4924 VYM.Open_mva200 200 Day MA
4927 VYM.High_YoY4 4 Year over 4 Year
4929 VYM.High_Smooth Savitsky-Golay Smoothed (p=3, n=365)
4931 VYM.High_SmoothDer Derivative of Smoothed
4933 VYM.High_mva200 200 Day MA
4938 VYM.Low_Smooth Savitsky-Golay Smoothed (p=3, n=365)
4940 VYM.Low_SmoothDer Derivative of Smoothed
4942 VYM.Low_mva200 200 Day MA
4947 VYM.Close_Smooth Savitsky-Golay Smoothed (p=3, n=365)
4949 VYM.Close_SmoothDer Derivative of Smoothed
4951 VYM.Close_mva200 200 Day MA
4956 VYM.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
4958 VYM.Volume_SmoothDer Derivative of Smoothed
4960 VYM.Volume_mva200 200 Day MA
4965 VYM.Adjusted_Smooth Savitsky-Golay Smoothed (p=3, n=365)
4967 VYM.Adjusted_SmoothDer Derivative of Smoothed
4969 VYM.Adjusted_mva200 200 Day MA
5012 ACWI.Volume_SmoothDer Derivative of Smoothed
5014 ACWI.Volume_mva200 200 Day MA
5030 SLY.Open_SmoothDer Derivative of Smoothed
5039 SLY.High_SmoothDer Derivative of Smoothed
5048 SLY.Low_SmoothDer Derivative of Smoothed
5057 SLY.Close_SmoothDer Derivative of Smoothed
5066 SLY.Volume_SmoothDer Derivative of Smoothed
5067 SLY.Volume_Log Log of
5068 SLY.Volume_mva200 200 Day MA
5075 SLY.Adjusted_SmoothDer Derivative of Smoothed
5118 QQQ.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5120 QQQ.Volume_SmoothDer Derivative of Smoothed
5122 QQQ.Volume_mva200 200 Day MA
5172 HYMB.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5174 HYMB.Volume_SmoothDer Derivative of Smoothed
5175 HYMB.Volume_Log Log of
5176 HYMB.Volume_mva200 200 Day MA
5190 GOLD.Open_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5191 GOLD.Open_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
5192 GOLD.Open_SmoothDer Derivative of Smoothed
5193 GOLD.Open_Log Log of
5195 GOLD.Open_mva050 50 Day MA
5199 GOLD.High_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5201 GOLD.High_SmoothDer Derivative of Smoothed
5204 GOLD.High_mva050 50 Day MA
5208 GOLD.Low_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5209 GOLD.Low_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
5210 GOLD.Low_SmoothDer Derivative of Smoothed
5213 GOLD.Low_mva050 50 Day MA
5217 GOLD.Close_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5219 GOLD.Close_SmoothDer Derivative of Smoothed
5222 GOLD.Close_mva050 50 Day MA
5226 GOLD.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5228 GOLD.Volume_SmoothDer Derivative of Smoothed
5229 GOLD.Volume_Log Log of
5231 GOLD.Volume_mva050 50 Day MA
5235 GOLD.Adjusted_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5237 GOLD.Adjusted_SmoothDer Derivative of Smoothed
5240 GOLD.Adjusted_mva050 50 Day MA
5242 BKR.Open_YoY4 4 Year over 4 Year
5244 BKR.Open_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5245 BKR.Open_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
5246 BKR.Open_SmoothDer Derivative of Smoothed
5247 BKR.Open_Log Log of
5248 BKR.Open_mva200 200 Day MA
5249 BKR.Open_mva050 50 Day MA
5251 BKR.High_YoY4 4 Year over 4 Year
5252 BKR.High_YoY5 5 Year over 5 Year
5253 BKR.High_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5254 BKR.High_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
5255 BKR.High_SmoothDer Derivative of Smoothed
5256 BKR.High_Log Log of
5257 BKR.High_mva200 200 Day MA
5258 BKR.High_mva050 50 Day MA
5260 BKR.Low_YoY4 4 Year over 4 Year
5262 BKR.Low_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5263 BKR.Low_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
5264 BKR.Low_SmoothDer Derivative of Smoothed
5265 BKR.Low_Log Log of
5266 BKR.Low_mva200 200 Day MA
5267 BKR.Low_mva050 50 Day MA
5271 BKR.Close_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5272 BKR.Close_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
5273 BKR.Close_SmoothDer Derivative of Smoothed
5274 BKR.Close_Log Log of
5275 BKR.Close_mva200 200 Day MA
5276 BKR.Close_mva050 50 Day MA
5280 BKR.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5282 BKR.Volume_SmoothDer Derivative of Smoothed
5283 BKR.Volume_Log Log of
5284 BKR.Volume_mva200 200 Day MA
5285 BKR.Volume_mva050 50 Day MA
5289 BKR.Adjusted_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5290 BKR.Adjusted_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
5291 BKR.Adjusted_SmoothDer Derivative of Smoothed
5292 BKR.Adjusted_Log Log of
5293 BKR.Adjusted_mva200 200 Day MA
5294 BKR.Adjusted_mva050 50 Day MA
5296 SLB.Open_YoY4 4 Year over 4 Year
5298 SLB.Open_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5299 SLB.Open_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
5300 SLB.Open_SmoothDer Derivative of Smoothed
5302 SLB.Open_mva200 200 Day MA
5303 SLB.Open_mva050 50 Day MA
5305 SLB.High_YoY4 4 Year over 4 Year
5307 SLB.High_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5308 SLB.High_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
5309 SLB.High_SmoothDer Derivative of Smoothed
5311 SLB.High_mva200 200 Day MA
5312 SLB.High_mva050 50 Day MA
5314 SLB.Low_YoY4 4 Year over 4 Year
5316 SLB.Low_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5317 SLB.Low_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
5318 SLB.Low_SmoothDer Derivative of Smoothed
5320 SLB.Low_mva200 200 Day MA
5321 SLB.Low_mva050 50 Day MA
5325 SLB.Close_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5327 SLB.Close_SmoothDer Derivative of Smoothed
5329 SLB.Close_mva200 200 Day MA
5330 SLB.Close_mva050 50 Day MA
5334 SLB.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5336 SLB.Volume_SmoothDer Derivative of Smoothed
5338 SLB.Volume_mva200 200 Day MA
5339 SLB.Volume_mva050 50 Day MA
5343 SLB.Adjusted_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5345 SLB.Adjusted_SmoothDer Derivative of Smoothed
5347 SLB.Adjusted_mva200 200 Day MA
5348 SLB.Adjusted_mva050 50 Day MA
5351 HAL.Open_YoY5 5 Year over 5 Year
5352 HAL.Open_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5353 HAL.Open_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
5354 HAL.Open_SmoothDer Derivative of Smoothed
5355 HAL.Open_Log Log of
5356 HAL.Open_mva200 200 Day MA
5357 HAL.Open_mva050 50 Day MA
5360 HAL.High_YoY5 5 Year over 5 Year
5361 HAL.High_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5362 HAL.High_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
5363 HAL.High_SmoothDer Derivative of Smoothed
5365 HAL.High_mva200 200 Day MA
5366 HAL.High_mva050 50 Day MA
5369 HAL.Low_YoY5 5 Year over 5 Year
5370 HAL.Low_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5372 HAL.Low_SmoothDer Derivative of Smoothed
5374 HAL.Low_mva200 200 Day MA
5375 HAL.Low_mva050 50 Day MA
5378 HAL.Close_YoY5 5 Year over 5 Year
5379 HAL.Close_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5381 HAL.Close_SmoothDer Derivative of Smoothed
5383 HAL.Close_mva200 200 Day MA
5384 HAL.Close_mva050 50 Day MA
5388 HAL.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5390 HAL.Volume_SmoothDer Derivative of Smoothed
5391 HAL.Volume_Log Log of
5392 HAL.Volume_mva200 200 Day MA
5396 HAL.Adjusted_YoY5 5 Year over 5 Year
5397 HAL.Adjusted_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5399 HAL.Adjusted_SmoothDer Derivative of Smoothed
5401 HAL.Adjusted_mva200 200 Day MA
5402 HAL.Adjusted_mva050 50 Day MA
5409 IP.Open_Log Log of
5442 IP.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5444 IP.Volume_SmoothDer Derivative of Smoothed
5458 PKG.Open_YoY4 4 Year over 4 Year
5460 PKG.Open_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5462 PKG.Open_SmoothDer Derivative of Smoothed
5465 PKG.Open_mva050 50 Day MA
5469 PKG.High_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5471 PKG.High_SmoothDer Derivative of Smoothed
5474 PKG.High_mva050 50 Day MA
5478 PKG.Low_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5480 PKG.Low_SmoothDer Derivative of Smoothed
5483 PKG.Low_mva050 50 Day MA
5487 PKG.Close_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5489 PKG.Close_SmoothDer Derivative of Smoothed
5492 PKG.Close_mva050 50 Day MA
5498 PKG.Volume_SmoothDer Derivative of Smoothed
5505 PKG.Adjusted_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5507 PKG.Adjusted_SmoothDer Derivative of Smoothed
5510 PKG.Adjusted_mva050 50 Day MA
5514 UPS.Open_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5518 UPS.Open_mva200 200 Day MA
5523 UPS.High_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5527 UPS.High_mva200 200 Day MA
5532 UPS.Low_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5536 UPS.Low_mva200 200 Day MA
5541 UPS.Close_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5545 UPS.Close_mva200 200 Day MA
5550 UPS.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5552 UPS.Volume_SmoothDer Derivative of Smoothed
5559 UPS.Adjusted_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5563 UPS.Adjusted_mva200 200 Day MA
5604 FDX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5608 FDX.Volume_mva200 200 Day MA
5624 T.Open_SmoothDer Derivative of Smoothed
5625 T.Open_Log Log of
5633 T.High_SmoothDer Derivative of Smoothed
5642 T.Low_SmoothDer Derivative of Smoothed
5651 T.Close_SmoothDer Derivative of Smoothed
5660 T.Volume_SmoothDer Derivative of Smoothed
5669 T.Adjusted_SmoothDer Derivative of Smoothed
5676 VZ.Open_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5678 VZ.Open_SmoothDer Derivative of Smoothed
5685 VZ.High_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5687 VZ.High_SmoothDer Derivative of Smoothed
5696 VZ.Low_SmoothDer Derivative of Smoothed
5705 VZ.Close_SmoothDer Derivative of Smoothed
5712 VZ.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5714 VZ.Volume_SmoothDer Derivative of Smoothed
5716 VZ.Volume_mva200 200 Day MA
5721 VZ.Adjusted_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5723 VZ.Adjusted_SmoothDer Derivative of Smoothed
5732 ISMMANPMI_SmoothDer Derivative of Smoothed Institute of Supply Managment PMI Composite Index
5751 MULTPLSP500SALESQUARTER_Log Log of S&P 500 TTM Sales (Not Inflation Adjusted)
5752 MULTPLSP500SALESQUARTER_mva200 S&P 500 TTM Sales (Not Inflation Adjusted) 200 Day MA
5753 MULTPLSP500SALESQUARTER_mva050 S&P 500 TTM Sales (Not Inflation Adjusted) 50 Day MA
5754 MULTPLSP500DIVYIELDMONTH_YoY S&P 500 Dividend Yield by Month Year over Year
5756 MULTPLSP500DIVYIELDMONTH_YoY5 S&P 500 Dividend Yield by Month 5 Year over 5 Year
5757 MULTPLSP500DIVYIELDMONTH_Smooth Savitsky-Golay Smoothed (p=3, n=365) S&P 500 Dividend Yield by Month
5759 MULTPLSP500DIVYIELDMONTH_SmoothDer Derivative of Smoothed S&P 500 Dividend Yield by Month
5760 MULTPLSP500DIVYIELDMONTH_Log Log of S&P 500 Dividend Yield by Month
5762 MULTPLSP500DIVYIELDMONTH_mva050 S&P 500 Dividend Yield by Month 50 Day MA
5763 MULTPLSP500DIVMONTH_YoY S&P 500 Dividend by Month (Inflation Adjusted) Year over Year
5769 MULTPLSP500DIVMONTH_Log Log of S&P 500 Dividend by Month (Inflation Adjusted)
5770 MULTPLSP500DIVMONTH_mva200 S&P 500 Dividend by Month (Inflation Adjusted) 200 Day MA
5771 MULTPLSP500DIVMONTH_mva050 S&P 500 Dividend by Month (Inflation Adjusted) 50 Day MA
5775 CHRISCMEHG1_Smooth Savitsky-Golay Smoothed (p=3, n=365) Copper Futures, Continuous Contract #1 (HG1) (Front Month)
5777 CHRISCMEHG1_SmoothDer Derivative of Smoothed Copper Futures, Continuous Contract #1 (HG1) (Front Month)
5778 CHRISCMEHG1_Log Log of Copper Futures, Continuous Contract #1 (HG1) (Front Month)
5780 CHRISCMEHG1_mva050 Copper Futures, Continuous Contract #1 (HG1) (Front Month) 50 Day MA
5781 WWDIWLDISAIRGOODMTK1_YoY Air transport, freight Year over Year
5787 WWDIWLDISAIRGOODMTK1_Log Log of Air transport, freight
5788 WWDIWLDISAIRGOODMTK1_mva200 Air transport, freight 200 Day MA
5789 WWDIWLDISAIRGOODMTK1_mva050 Air transport, freight 50 Day MA
5793 LBMAGOLD.USD_AM_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5795 LBMAGOLD.USD_AM_SmoothDer Derivative of Smoothed
5797 LBMAGOLD.USD_AM_mva200 200 Day MA
5798 LBMAGOLD.USD_AM_mva050 50 Day MA
5802 LBMAGOLD.USD_PM_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5804 LBMAGOLD.USD_PM_SmoothDer Derivative of Smoothed
5806 LBMAGOLD.USD_PM_mva200 200 Day MA
5807 LBMAGOLD.USD_PM_mva050 50 Day MA
5811 LBMAGOLD.GBP_AM_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5813 LBMAGOLD.GBP_AM_SmoothDer Derivative of Smoothed
5815 LBMAGOLD.GBP_AM_mva200 200 Day MA
5816 LBMAGOLD.GBP_AM_mva050 50 Day MA
5820 LBMAGOLD.GBP_PM_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5822 LBMAGOLD.GBP_PM_SmoothDer Derivative of Smoothed
5824 LBMAGOLD.GBP_PM_mva200 200 Day MA
5825 LBMAGOLD.GBP_PM_mva050 50 Day MA
5829 LBMAGOLD.EURO_AM_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5831 LBMAGOLD.EURO_AM_SmoothDer Derivative of Smoothed
5833 LBMAGOLD.EURO_AM_mva200 200 Day MA
5834 LBMAGOLD.EURO_AM_mva050 50 Day MA
5838 LBMAGOLD.EURO_PM_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5840 LBMAGOLD.EURO_PM_SmoothDer Derivative of Smoothed
5842 LBMAGOLD.EURO_PM_mva200 200 Day MA
5843 LBMAGOLD.EURO_PM_mva050 50 Day MA
5844 BKRTotal_YoY Total Rig Count Year over Year
5850 BKRTotal_Log Log of Total Rig Count
5851 BKRTotal_mva200 Total Rig Count 200 Day MA
5852 BKRTotal_mva050 Total Rig Count 50 Day MA
5853 BKRGas_YoY Gas Rig Count Year over Year
5859 BKRGas_Log Log of Gas Rig Count
5860 BKRGas_mva200 Gas Rig Count 200 Day MA
5861 BKRGas_mva050 Gas Rig Count 50 Day MA
5862 BKROil_YoY Oil Rig Count Year over Year
5868 BKROil_Log Log of Oil Rig Count
5869 BKROil_mva200 Oil Rig Count 200 Day MA
5870 BKROil_mva050 Oil Rig Count 50 Day MA
5871 FARMINCOME_YoY Net Farm Income Year over Year
5877 FARMINCOME_Log Log of Net Farm Income
5878 FARMINCOME_mva200 Net Farm Income 200 Day MA
5879 FARMINCOME_mva050 Net Farm Income 50 Day MA
5883 OPEARNINGSPERSHARE_Smooth Savitsky-Golay Smoothed (p=3, n=365) Operating Earnings per Share
5885 OPEARNINGSPERSHARE_SmoothDer Derivative of Smoothed Operating Earnings per Share
5886 OPEARNINGSPERSHARE_Log Log of Operating Earnings per Share
5887 OPEARNINGSPERSHARE_mva200 Operating Earnings per Share 200 Day MA
5888 OPEARNINGSPERSHARE_mva050 Operating Earnings per Share 50 Day MA
5892 AREARNINGSPERSHARE_Smooth Savitsky-Golay Smoothed (p=3, n=365) As-Reported Earnings per Share
5894 AREARNINGSPERSHARE_SmoothDer Derivative of Smoothed As-Reported Earnings per Share
5895 AREARNINGSPERSHARE_Log Log of As-Reported Earnings per Share
5896 AREARNINGSPERSHARE_mva200 As-Reported Earnings per Share 200 Day MA
5897 AREARNINGSPERSHARE_mva050 As-Reported Earnings per Share 50 Day MA
5901 CASHDIVIDENDSPERSHR_Smooth Savitsky-Golay Smoothed (p=3, n=365) Cash Dividends per Share
5903 CASHDIVIDENDSPERSHR_SmoothDer Derivative of Smoothed Cash Dividends per Share
5904 CASHDIVIDENDSPERSHR_Log Log of Cash Dividends per Share
5905 CASHDIVIDENDSPERSHR_mva200 Cash Dividends per Share 200 Day MA
5906 CASHDIVIDENDSPERSHR_mva050 Cash Dividends per Share 50 Day MA
5912 SALESPERSHR_SmoothDer Derivative of Smoothed Sales per Share
5913 SALESPERSHR_Log Log of Sales per Share
5915 SALESPERSHR_mva050 Sales per Share 50 Day MA
5919 BOOKVALPERSHR_Smooth Savitsky-Golay Smoothed (p=3, n=365) Book value per Share
5921 BOOKVALPERSHR_SmoothDer Derivative of Smoothed Book value per Share
5922 BOOKVALPERSHR_Log Log of Book value per Share
5923 BOOKVALPERSHR_mva200 Book value per Share 200 Day MA
5924 BOOKVALPERSHR_mva050 Book value per Share 50 Day MA
5927 CAPEXPERSHR_YoY5 Cap ex per Share 5 Year over 5 Year
5931 CAPEXPERSHR_Log Log of Cap ex per Share
5933 CAPEXPERSHR_mva050 Cap ex per Share 50 Day MA
5937 PRICE_Smooth Savitsky-Golay Smoothed (p=3, n=365) Price
5939 PRICE_SmoothDer Derivative of Smoothed Price
5940 PRICE_Log Log of Price
5941 PRICE_mva200 Price 200 Day MA
5942 PRICE_mva050 Price 50 Day MA
5946 OPEARNINGSTTM_Smooth Savitsky-Golay Smoothed (p=3, n=365) TTM Operating Earnings
5948 OPEARNINGSTTM_SmoothDer Derivative of Smoothed TTM Operating Earnings
5949 OPEARNINGSTTM_Log Log of TTM Operating Earnings
5950 OPEARNINGSTTM_mva200 TTM Operating Earnings 200 Day MA
5951 OPEARNINGSTTM_mva050 TTM Operating Earnings 50 Day MA
5955 AREARNINGSTTM_Smooth Savitsky-Golay Smoothed (p=3, n=365) TTM Reported Earnings
5957 AREARNINGSTTM_SmoothDer Derivative of Smoothed TTM Reported Earnings
5958 AREARNINGSTTM_Log Log of TTM Reported Earnings
5959 AREARNINGSTTM_mva200 TTM Reported Earnings 200 Day MA
5960 AREARNINGSTTM_mva050 TTM Reported Earnings 50 Day MA
5971 FINRAFreeCreditMargin_YoY4 Free Credit Balances in Customers’ Securities Margin Accounts 4 Year over 4 Year
5973 FINRAFreeCreditMargin_Smooth Savitsky-Golay Smoothed (p=3, n=365) Free Credit Balances in Customers’ Securities Margin Accounts
5975 FINRAFreeCreditMargin_SmoothDer Derivative of Smoothed Free Credit Balances in Customers’ Securities Margin Accounts
5976 FINRAFreeCreditMargin_Log Log of Free Credit Balances in Customers’ Securities Margin Accounts
5978 FINRAFreeCreditMargin_mva050 Free Credit Balances in Customers’ Securities Margin Accounts 50 Day MA
5979 OCCEquityVolume_YoY Equity Options Volume Year over Year
5985 OCCEquityVolume_Log Log of Equity Options Volume
5986 OCCEquityVolume_mva200 Equity Options Volume 200 Day MA
5987 OCCEquityVolume_mva050 Equity Options Volume 50 Day MA
5988 OCCNonEquityVolume_YoY Non-Equity Options Volume Year over Year
5994 OCCNonEquityVolume_Log Log of Non-Equity Options Volume
5995 OCCNonEquityVolume_mva200 Non-Equity Options Volume 200 Day MA
5996 OCCNonEquityVolume_mva050 Non-Equity Options Volume 50 Day MA
6000 RSALESAGG_Smooth Savitsky-Golay Smoothed (p=3, n=365) Real Retail and Food Services Sales (RRSFS and RSALES)
6002 RSALESAGG_SmoothDer Derivative of Smoothed Real Retail and Food Services Sales (RRSFS and RSALES)
6012 BUSLOANS.minus.BUSLOANSNSA_Log Log of Business Loans (Montlhy) SA - NSA
6021 BUSLOANS.minus.BUSLOANSNSA.by.GDP_Log Log of Business Loans (Montlhy) SA - NSA divided by GDP
6024 BUSLOANS.by.GDP_YoY Business Loans Normalized by GDP Year over Year
6026 BUSLOANS.by.GDP_YoY5 Business Loans Normalized by GDP 5 Year over 5 Year
6027 BUSLOANS.by.GDP_Smooth Savitsky-Golay Smoothed (p=3, n=365) Business Loans Normalized by GDP
6029 BUSLOANS.by.GDP_SmoothDer Derivative of Smoothed Business Loans Normalized by GDP
6030 BUSLOANS.by.GDP_Log Log of Business Loans Normalized by GDP
6032 BUSLOANS.by.GDP_mva050 Business Loans Normalized by GDP 50 Day MA
6036 BUSLOANS.INTEREST_Smooth Savitsky-Golay Smoothed (p=3, n=365) Business Loans (Monthly, SA) Adjusted Interest Burdens
6037 BUSLOANS.INTEREST_Smooth.short Savitsky-Golay Smoothed (p=3, n=15) Business Loans (Monthly, SA) Adjusted Interest Burdens
6038 BUSLOANS.INTEREST_SmoothDer Derivative of Smoothed Business Loans (Monthly, SA) Adjusted Interest Burdens
6040 BUSLOANS.INTEREST_mva200 Business Loans (Monthly, SA) Adjusted Interest Burdens 200 Day MA
6041 BUSLOANS.INTEREST_mva050 Business Loans (Monthly, SA) Adjusted Interest Burdens 50 Day MA
6045 BUSLOANS.INTEREST.by.GDP_Smooth Savitsky-Golay Smoothed (p=3, n=365) Business Loans (Monthly, SA) Adjusted Interest Burden Divided by GDP
6046 BUSLOANS.INTEREST.by.GDP_Smooth.short Savitsky-Golay Smoothed (p=3, n=15) Business Loans (Monthly, SA) Adjusted Interest Burden Divided by GDP
6047 BUSLOANS.INTEREST.by.GDP_SmoothDer Derivative of Smoothed Business Loans (Monthly, SA) Adjusted Interest Burden Divided by GDP
6049 BUSLOANS.INTEREST.by.GDP_mva200 Business Loans (Monthly, SA) Adjusted Interest Burden Divided by GDP 200 Day MA
6050 BUSLOANS.INTEREST.by.GDP_mva050 Business Loans (Monthly, SA) Adjusted Interest Burden Divided by GDP 50 Day MA
6051 BUSLOANSNSA.by.GDP_YoY Business Loans Normalized by GDP Year over Year
6054 BUSLOANSNSA.by.GDP_Smooth Savitsky-Golay Smoothed (p=3, n=365) Business Loans Normalized by GDP
6056 BUSLOANSNSA.by.GDP_SmoothDer Derivative of Smoothed Business Loans Normalized by GDP
6057 BUSLOANSNSA.by.GDP_Log Log of Business Loans Normalized by GDP
6059 BUSLOANSNSA.by.GDP_mva050 Business Loans Normalized by GDP 50 Day MA
6060 TOTCI.by.GDP_YoY Business Loans (Weekly, SA) Normalized by GDP Year over Year
6062 TOTCI.by.GDP_YoY5 Business Loans (Weekly, SA) Normalized by GDP 5 Year over 5 Year
6063 TOTCI.by.GDP_Smooth Savitsky-Golay Smoothed (p=3, n=365) Business Loans (Weekly, SA) Normalized by GDP
6065 TOTCI.by.GDP_SmoothDer Derivative of Smoothed Business Loans (Weekly, SA) Normalized by GDP
6068 TOTCI.by.GDP_mva050 Business Loans (Weekly, SA) Normalized by GDP 50 Day MA
6071 TOTCINSA.by.GDP_YoY5 Business Loans (Weekly, NSA) Normalized by GDP 5 Year over 5 Year
6072 TOTCINSA.by.GDP_Smooth Savitsky-Golay Smoothed (p=3, n=365) Business Loans (Weekly, NSA) Normalized by GDP
6074 TOTCINSA.by.GDP_SmoothDer Derivative of Smoothed Business Loans (Weekly, NSA) Normalized by GDP
6075 TOTCINSA.by.GDP_Log Log of Business Loans (Weekly, NSA) Normalized by GDP
6077 TOTCINSA.by.GDP_mva050 Business Loans (Weekly, NSA) Normalized by GDP 50 Day MA
6081 TOTCINSA.INTEREST_Smooth Savitsky-Golay Smoothed (p=3, n=365) Business Loans (Weekly, NSA) Adjusted Interest Burdens
6082 TOTCINSA.INTEREST_Smooth.short Savitsky-Golay Smoothed (p=3, n=15) Business Loans (Weekly, NSA) Adjusted Interest Burdens
6083 TOTCINSA.INTEREST_SmoothDer Derivative of Smoothed Business Loans (Weekly, NSA) Adjusted Interest Burdens
6085 TOTCINSA.INTEREST_mva200 Business Loans (Weekly, NSA) Adjusted Interest Burdens 200 Day MA
6086 TOTCINSA.INTEREST_mva050 Business Loans (Weekly, NSA) Adjusted Interest Burdens 50 Day MA
6090 TOTCINSA.INTEREST.by.GDP_Smooth Savitsky-Golay Smoothed (p=3, n=365) Business Loans (weekly, NSA) Adjusted Interest Burden Divided by GDP
6091 TOTCINSA.INTEREST.by.GDP_Smooth.short Savitsky-Golay Smoothed (p=3, n=15) Business Loans (weekly, NSA) Adjusted Interest Burden Divided by GDP
6092 TOTCINSA.INTEREST.by.GDP_SmoothDer Derivative of Smoothed Business Loans (weekly, NSA) Adjusted Interest Burden Divided by GDP
6094 TOTCINSA.INTEREST.by.GDP_mva200 Business Loans (weekly, NSA) Adjusted Interest Burden Divided by GDP 200 Day MA
6095 TOTCINSA.INTEREST.by.GDP_mva050 Business Loans (weekly, NSA) Adjusted Interest Burden Divided by GDP 50 Day MA
6096 W875RX1.by.GDP_YoY Real Personal Income Normalized by GDP Year over Year
6097 W875RX1.by.GDP_YoY4 Real Personal Income Normalized by GDP 4 Year over 4 Year
6101 W875RX1.by.GDP_SmoothDer Derivative of Smoothed Real Personal Income Normalized by GDP
6105 A065RC1A027NBEA.by.GDP_YoY Personal Income (NSA) Normalized by GDP Year over Year
6106 A065RC1A027NBEA.by.GDP_YoY4 Personal Income (NSA) Normalized by GDP 4 Year over 4 Year
6110 A065RC1A027NBEA.by.GDP_SmoothDer Derivative of Smoothed Personal Income (NSA) Normalized by GDP
6115 PI.by.GDP_YoY4 Personal Income (SA) Normalized by GDP 4 Year over 4 Year
6117 PI.by.GDP_Smooth Savitsky-Golay Smoothed (p=3, n=365) Personal Income (SA) Normalized by GDP
6119 PI.by.GDP_SmoothDer Derivative of Smoothed Personal Income (SA) Normalized by GDP
6120 PI.by.GDP_Log Log of Personal Income (SA) Normalized by GDP
6122 PI.by.GDP_mva050 Personal Income (SA) Normalized by GDP 50 Day MA
6125 A053RC1Q027SBEA.by.GDP_YoY5 National income: Corporate profits before tax (without IVA and CCAdj) Normalized by GDP 5 Year over 5 Year
6128 A053RC1Q027SBEA.by.GDP_SmoothDer Derivative of Smoothed National income: Corporate profits before tax (without IVA and CCAdj) Normalized by GDP
6137 CPROFIT.by.GDP_SmoothDer Derivative of Smoothed National income: Corporate profits before tax (with IVA and CCAdj) Normalized by GDP
6141 CONSUMERNSA.by.GDP_YoY Consumer Loans Not Seasonally Adjusted divided by GDP Year over Year
6144 CONSUMERNSA.by.GDP_Smooth Savitsky-Golay Smoothed (p=3, n=365) Consumer Loans Not Seasonally Adjusted divided by GDP
6148 CONSUMERNSA.by.GDP_mva200 Consumer Loans Not Seasonally Adjusted divided by GDP 200 Day MA
6150 RREACBM027NBOG.by.GDP_YoY Residental Real Estate Loans (Monthly, NSA) divided by GDP Year over Year
6151 RREACBM027NBOG.by.GDP_YoY4 Residental Real Estate Loans (Monthly, NSA) divided by GDP 4 Year over 4 Year
6152 RREACBM027NBOG.by.GDP_YoY5 Residental Real Estate Loans (Monthly, NSA) divided by GDP 5 Year over 5 Year
6153 RREACBM027NBOG.by.GDP_Smooth Savitsky-Golay Smoothed (p=3, n=365) Residental Real Estate Loans (Monthly, NSA) divided by GDP
6159 RREACBM027SBOG.by.GDP_YoY Residental Real Estate Loans (Monthly, SA) divided by GDP Year over Year
6160 RREACBM027SBOG.by.GDP_YoY4 Residental Real Estate Loans (Monthly, SA) divided by GDP 4 Year over 4 Year
6161 RREACBM027SBOG.by.GDP_YoY5 Residental Real Estate Loans (Monthly, SA) divided by GDP 5 Year over 5 Year
6162 RREACBM027SBOG.by.GDP_Smooth Savitsky-Golay Smoothed (p=3, n=365) Residental Real Estate Loans (Monthly, SA) divided by GDP
6164 RREACBM027SBOG.by.GDP_SmoothDer Derivative of Smoothed Residental Real Estate Loans (Monthly, SA) divided by GDP
6165 RREACBM027SBOG.by.GDP_Log Log of Residental Real Estate Loans (Monthly, SA) divided by GDP
6167 RREACBM027SBOG.by.GDP_mva050 Residental Real Estate Loans (Monthly, SA) divided by GDP 50 Day MA
6168 RREACBW027SBOG.by.GDP_YoY Residental Real Estate Loans (Weekly, SA) divided by GDP Year over Year
6170 RREACBW027SBOG.by.GDP_YoY5 Residental Real Estate Loans (Weekly, SA) divided by GDP 5 Year over 5 Year
6171 RREACBW027SBOG.by.GDP_Smooth Savitsky-Golay Smoothed (p=3, n=365) Residental Real Estate Loans (Weekly, SA) divided by GDP
6173 RREACBW027SBOG.by.GDP_SmoothDer Derivative of Smoothed Residental Real Estate Loans (Weekly, SA) divided by GDP
6174 RREACBW027SBOG.by.GDP_Log Log of Residental Real Estate Loans (Weekly, SA) divided by GDP
6176 RREACBW027SBOG.by.GDP_mva050 Residental Real Estate Loans (Weekly, SA) divided by GDP 50 Day MA
6177 RREACBW027NBOG.by.GDP_YoY Residental Real Estate Loans (Weekly, NSA) divided by GDP Year over Year
6180 RREACBW027NBOG.by.GDP_Smooth Savitsky-Golay Smoothed (p=3, n=365) Residental Real Estate Loans (Weekly, NSA) divided by GDP
6182 RREACBW027NBOG.by.GDP_SmoothDer Derivative of Smoothed Residental Real Estate Loans (Weekly, NSA) divided by GDP
6185 RREACBW027NBOG.by.GDP_mva050 Residental Real Estate Loans (Weekly, NSA) divided by GDP 50 Day MA
6191 UMDMNO.by.GDP_SmoothDer Derivative of Smoothed Durable Goods (Monthly, NSA) divided by GDP
6200 DGORDER.by.GDP_SmoothDer Derivative of Smoothed Durable Goods (Monthly, NSA) divided by GDP
6202 DGORDER.by.GDP_mva200 Durable Goods (Monthly, NSA) divided by GDP 200 Day MA
6204 ASHMA.by.GDP_YoY Home Mortgages (Quarterly, NSA) divided by GDP Year over Year
6205 ASHMA.by.GDP_YoY4 Home Mortgages (Quarterly, NSA) divided by GDP 4 Year over 4 Year
6206 ASHMA.by.GDP_YoY5 Home Mortgages (Quarterly, NSA) divided by GDP 5 Year over 5 Year
6209 ASHMA.by.GDP_SmoothDer Derivative of Smoothed Home Mortgages (Quarterly, NSA) divided by GDP
6214 ASHMA.INTEREST_YoY4 Home Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens 4 Year over 4 Year
6215 ASHMA.INTEREST_YoY5 Home Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens 5 Year over 5 Year
6216 ASHMA.INTEREST_Smooth Savitsky-Golay Smoothed (p=3, n=365) Home Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens
6217 ASHMA.INTEREST_Smooth.short Savitsky-Golay Smoothed (p=3, n=15) Home Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens
6218 ASHMA.INTEREST_SmoothDer Derivative of Smoothed Home Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens
6219 ASHMA.INTEREST_Log Log of Home Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens
6220 ASHMA.INTEREST_mva200 Home Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens 200 Day MA
6221 ASHMA.INTEREST_mva050 Home Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens 50 Day MA
6223 ASHMA.INTEREST.by.GDP_YoY4 4 Year over 4 Year
6224 ASHMA.INTEREST.by.GDP_YoY5 5 Year over 5 Year
6225 ASHMA.INTEREST.by.GDP_Smooth Savitsky-Golay Smoothed (p=3, n=365)
6226 ASHMA.INTEREST.by.GDP_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
6227 ASHMA.INTEREST.by.GDP_SmoothDer Derivative of Smoothed
6228 ASHMA.INTEREST.by.GDP_Log Log of
6229 ASHMA.INTEREST.by.GDP_mva200 200 Day MA
6230 ASHMA.INTEREST.by.GDP_mva050 50 Day MA
6234 CONSUMERNSA.INTEREST_Smooth Savitsky-Golay Smoothed (p=3, n=365) Consumer Loans (Not Seasonally Adjusted) Interest Burdens
6238 CONSUMERNSA.INTEREST_mva200 Consumer Loans (Not Seasonally Adjusted) Interest Burdens 200 Day MA
6240 CONSUMERNSA.INTEREST.by.GDP_YoY Consumer Loans (Not Seasonally Adjusted) Interest Burden Divided by GDP Year over Year
6243 CONSUMERNSA.INTEREST.by.GDP_Smooth Savitsky-Golay Smoothed (p=3, n=365) Consumer Loans (Not Seasonally Adjusted) Interest Burden Divided by GDP
6249 TOTLNNSA_YoY Total Loans Not Seasonally Adjusted (BUSLOANS+REALLNSA+CONSUMERNSA) Year over Year
6255 TOTLNNSA_Log Log of Total Loans Not Seasonally Adjusted (BUSLOANS+REALLNSA+CONSUMERNSA)
6256 TOTLNNSA_mva200 Total Loans Not Seasonally Adjusted (BUSLOANS+REALLNSA+CONSUMERNSA) 200 Day MA
6257 TOTLNNSA_mva050 Total Loans Not Seasonally Adjusted (BUSLOANS+REALLNSA+CONSUMERNSA) 50 Day MA
6258 TOTLNNSA.by.GDP_YoY Total Loans Not Seasonally Adjusted divided by GDP Year over Year
6261 TOTLNNSA.by.GDP_Smooth Savitsky-Golay Smoothed (p=3, n=365) Total Loans Not Seasonally Adjusted divided by GDP
6263 TOTLNNSA.by.GDP_SmoothDer Derivative of Smoothed Total Loans Not Seasonally Adjusted divided by GDP
6264 TOTLNNSA.by.GDP_Log Log of Total Loans Not Seasonally Adjusted divided by GDP
6266 TOTLNNSA.by.GDP_mva050 Total Loans Not Seasonally Adjusted divided by GDP 50 Day MA
6270 TOTLNNSA.INTEREST_Smooth Savitsky-Golay Smoothed (p=3, n=365) Total Loans Not Seasonally Adjusted Interest Burdens
6271 TOTLNNSA.INTEREST_Smooth.short Savitsky-Golay Smoothed (p=3, n=15) Total Loans Not Seasonally Adjusted Interest Burdens
6272 TOTLNNSA.INTEREST_SmoothDer Derivative of Smoothed Total Loans Not Seasonally Adjusted Interest Burdens
6274 TOTLNNSA.INTEREST_mva200 Total Loans Not Seasonally Adjusted Interest Burdens 200 Day MA
6275 TOTLNNSA.INTEREST_mva050 Total Loans Not Seasonally Adjusted Interest Burdens 50 Day MA
6279 TOTLNNSA.INTEREST.by.GDP_Smooth Savitsky-Golay Smoothed (p=3, n=365) Total Loans Not Seasonally Adjusted Interest Burden Divided by GDP
6280 TOTLNNSA.INTEREST.by.GDP_Smooth.short Savitsky-Golay Smoothed (p=3, n=15) Total Loans Not Seasonally Adjusted Interest Burden Divided by GDP
6281 TOTLNNSA.INTEREST.by.GDP_SmoothDer Derivative of Smoothed Total Loans Not Seasonally Adjusted Interest Burden Divided by GDP
6283 TOTLNNSA.INTEREST.by.GDP_mva200 Total Loans Not Seasonally Adjusted Interest Burden Divided by GDP 200 Day MA
6284 TOTLNNSA.INTEREST.by.GDP_mva050 Total Loans Not Seasonally Adjusted Interest Burden Divided by GDP 50 Day MA
6294 EXCSRESNW.by.GDP_YoY Excess Reserves of Depository Institutions Divided by GDP Year over Year
6295 EXCSRESNW.by.GDP_YoY4 Excess Reserves of Depository Institutions Divided by GDP 4 Year over 4 Year
6299 EXCSRESNW.by.GDP_SmoothDer Derivative of Smoothed Excess Reserves of Depository Institutions Divided by GDP
6307 WLRRAL.by.GDP_Smooth.short Savitsky-Golay Smoothed (p=3, n=15) Liabilities and Capital: Liabilities: Reverse Repurchase Agreements: Wednesday Level (NSA) Divided by GDP
6309 WLRRAL.by.GDP_Log Log of Liabilities and Capital: Liabilities: Reverse Repurchase Agreements: Wednesday Level (NSA) Divided by GDP
6310 WLRRAL.by.GDP_mva200 Liabilities and Capital: Liabilities: Reverse Repurchase Agreements: Wednesday Level (NSA) Divided by GDP 200 Day MA
6315 SOFR99.minus.SOFR1_Smooth Savitsky-Golay Smoothed (p=3, n=365) Secured Overnight Financing Rate: 99th Percentile - 1st Percentile
6317 SOFR99.minus.SOFR1_SmoothDer Derivative of Smoothed Secured Overnight Financing Rate: 99th Percentile - 1st Percentile
6320 SOFR99.minus.SOFR1_mva050 Secured Overnight Financing Rate: 99th Percentile - 1st Percentile 50 Day MA
6326 EXPCH.minus.IMPCH_SmoothDer Derivative of Smoothed U.S. Exports to China (FAS Basis) - U.S. Imports to China (Customs Basis)
6327 EXPCH.minus.IMPCH_Log Log of U.S. Exports to China (FAS Basis) - U.S. Imports to China (Customs Basis)
6333 EXPMX.minus.IMPMX_Smooth Savitsky-Golay Smoothed (p=3, n=365)
6335 EXPMX.minus.IMPMX_SmoothDer Derivative of Smoothed
6336 EXPMX.minus.IMPMX_Log Log of
6340 SRPSABSNNCB.by.GDP_YoY4 Nonfinancial corporate business; security repurchase agreements; asset, Level (NSA) Divided by GDP 4 Year over 4 Year
6341 SRPSABSNNCB.by.GDP_YoY5 Nonfinancial corporate business; security repurchase agreements; asset, Level (NSA) Divided by GDP 5 Year over 5 Year
6344 SRPSABSNNCB.by.GDP_SmoothDer Derivative of Smoothed Nonfinancial corporate business; security repurchase agreements; asset, Level (NSA) Divided by GDP
6345 SRPSABSNNCB.by.GDP_Log Log of Nonfinancial corporate business; security repurchase agreements; asset, Level (NSA) Divided by GDP
6346 SRPSABSNNCB.by.GDP_mva200 Nonfinancial corporate business; security repurchase agreements; asset, Level (NSA) Divided by GDP 200 Day MA
6347 SRPSABSNNCB.by.GDP_mva050 Nonfinancial corporate business; security repurchase agreements; asset, Level (NSA) Divided by GDP 50 Day MA
6348 ASTLL.by.GDP_YoY All sectors; total loans; liability, Level (NSA) Divided by GDP Year over Year
6353 ASTLL.by.GDP_SmoothDer Derivative of Smoothed All sectors; total loans; liability, Level (NSA) Divided by GDP
6357 ASFMA.by.GDP_YoY All sectors; farm mortgages; asset, Level (NSA) Divided by GDP Year over Year
6358 ASFMA.by.GDP_YoY4 All sectors; farm mortgages; asset, Level (NSA) Divided by GDP 4 Year over 4 Year
6362 ASFMA.by.GDP_SmoothDer Derivative of Smoothed All sectors; farm mortgages; asset, Level (NSA) Divided by GDP
6366 ASFMA.by.ASTLL_YoY All sectors; total loans Divided by farm mortgages Year over Year
6368 ASFMA.by.ASTLL_YoY5 All sectors; total loans Divided by farm mortgages 5 Year over 5 Year
6371 ASFMA.by.ASTLL_SmoothDer Derivative of Smoothed All sectors; total loans Divided by farm mortgages
6376 ASFMA.INTEREST_YoY4 Farm Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens 4 Year over 4 Year
6377 ASFMA.INTEREST_YoY5 Farm Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens 5 Year over 5 Year
6378 ASFMA.INTEREST_Smooth Savitsky-Golay Smoothed (p=3, n=365) Farm Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens
6379 ASFMA.INTEREST_Smooth.short Savitsky-Golay Smoothed (p=3, n=15) Farm Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens
6380 ASFMA.INTEREST_SmoothDer Derivative of Smoothed Farm Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens
6381 ASFMA.INTEREST_Log Log of Farm Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens
6382 ASFMA.INTEREST_mva200 Farm Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens 200 Day MA
6383 ASFMA.INTEREST_mva050 Farm Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens 50 Day MA
6385 ASFMA.INTEREST.by.GDP_YoY4 Farm Mortgages (Quarterly, NSA) Interest Burden Divided by GDP 4 Year over 4 Year
6386 ASFMA.INTEREST.by.GDP_YoY5 Farm Mortgages (Quarterly, NSA) Interest Burden Divided by GDP 5 Year over 5 Year
6387 ASFMA.INTEREST.by.GDP_Smooth Savitsky-Golay Smoothed (p=3, n=365) Farm Mortgages (Quarterly, NSA) Interest Burden Divided by GDP
6388 ASFMA.INTEREST.by.GDP_Smooth.short Savitsky-Golay Smoothed (p=3, n=15) Farm Mortgages (Quarterly, NSA) Interest Burden Divided by GDP
6389 ASFMA.INTEREST.by.GDP_SmoothDer Derivative of Smoothed Farm Mortgages (Quarterly, NSA) Interest Burden Divided by GDP
6390 ASFMA.INTEREST.by.GDP_Log Log of Farm Mortgages (Quarterly, NSA) Interest Burden Divided by GDP
6391 ASFMA.INTEREST.by.GDP_mva200 Farm Mortgages (Quarterly, NSA) Interest Burden Divided by GDP 200 Day MA
6392 ASFMA.INTEREST.by.GDP_mva050 Farm Mortgages (Quarterly, NSA) Interest Burden Divided by GDP 50 Day MA
6393 FARMINCOME.by.GDP_YoY Farm Income (Annual, NSA) Divided by GDP Year over Year
6398 FARMINCOME.by.GDP_SmoothDer Derivative of Smoothed Farm Income (Annual, NSA) Divided by GDP
6412 WALCL.by.GDP_YoY4 All Federal Reserve Banks: Total Assets Divided by GDP 4 Year over 4 Year
6413 WALCL.by.GDP_YoY5 All Federal Reserve Banks: Total Assets Divided by GDP 5 Year over 5 Year
6414 WALCL.by.GDP_Smooth Savitsky-Golay Smoothed (p=3, n=365) All Federal Reserve Banks: Total Assets Divided by GDP
6415 WALCL.by.GDP_Smooth.short Savitsky-Golay Smoothed (p=3, n=15) All Federal Reserve Banks: Total Assets Divided by GDP
6416 WALCL.by.GDP_SmoothDer Derivative of Smoothed All Federal Reserve Banks: Total Assets Divided by GDP
6417 WALCL.by.GDP_Log Log of All Federal Reserve Banks: Total Assets Divided by GDP
6418 WALCL.by.GDP_mva200 All Federal Reserve Banks: Total Assets Divided by GDP 200 Day MA
6419 WALCL.by.GDP_mva050 All Federal Reserve Banks: Total Assets Divided by GDP 50 Day MA
6420 ECBASSETS.by.EUNNGDP_YoY Central Bank Assets for Euro Area (11-19 Countries) Divided by GDP Year over Year
6425 ECBASSETS.by.EUNNGDP_SmoothDer Derivative of Smoothed Central Bank Assets for Euro Area (11-19 Countries) Divided by GDP
6434 DGS30TO10_SmoothDer Derivative of Smoothed Yield Curve, 30 and 10 Year Treasury (DGS30-DGS10)
6435 DGS30TO10_Log Log of Yield Curve, 30 and 10 Year Treasury (DGS30-DGS10)
6444 DGS10TO1_Log Log of Yield Curve, 10 and 1 Year Treasury (DGS10-DGS1)
6453 DGS10TO2_Log Log of Yield Curve, 10 and 2 Year Treasury (DGS10-DGS2)
6459 DGS10TOTB3MS_Smooth Savitsky-Golay Smoothed (p=3, n=365) Yield Curve, 10 and 3 Month Treasury (DGS10-TB3MS)
6460 DGS10TOTB3MS_Smooth.short Savitsky-Golay Smoothed (p=3, n=15) Yield Curve, 10 and 3 Month Treasury (DGS10-TB3MS)
6461 DGS10TOTB3MS_SmoothDer Derivative of Smoothed Yield Curve, 10 and 3 Month Treasury (DGS10-TB3MS)
6462 DGS10TOTB3MS_Log Log of Yield Curve, 10 and 3 Month Treasury (DGS10-TB3MS)
6463 DGS10TOTB3MS_mva200 Yield Curve, 10 and 3 Month Treasury (DGS10-TB3MS) 200 Day MA
6464 DGS10TOTB3MS_mva050 Yield Curve, 10 and 3 Month Treasury (DGS10-TB3MS) 50 Day MA
6466 DGS10TODTB3_YoY4 Yield Curve, 10 and 3 Month Treasury (DGS10-DTB3) 4 Year over 4 Year
6468 DGS10TODTB3_Smooth Savitsky-Golay Smoothed (p=3, n=365) Yield Curve, 10 and 3 Month Treasury (DGS10-DTB3)
6469 DGS10TODTB3_Smooth.short Savitsky-Golay Smoothed (p=3, n=15) Yield Curve, 10 and 3 Month Treasury (DGS10-DTB3)
6470 DGS10TODTB3_SmoothDer Derivative of Smoothed Yield Curve, 10 and 3 Month Treasury (DGS10-DTB3)
6471 DGS10TODTB3_Log Log of Yield Curve, 10 and 3 Month Treasury (DGS10-DTB3)
6472 DGS10TODTB3_mva200 Yield Curve, 10 and 3 Month Treasury (DGS10-DTB3) 200 Day MA
6473 DGS10TODTB3_mva050 Yield Curve, 10 and 3 Month Treasury (DGS10-DTB3) 50 Day MA
6483 LNU03000000BYPOPTHM_YoY Unemployment level (NSA) / Population Year over Year
6484 LNU03000000BYPOPTHM_YoY4 Unemployment level (NSA) / Population 4 Year over 4 Year
6485 LNU03000000BYPOPTHM_YoY5 Unemployment level (NSA) / Population 5 Year over 5 Year
6486 LNU03000000BYPOPTHM_Smooth Savitsky-Golay Smoothed (p=3, n=365) Unemployment level (NSA) / Population
6488 LNU03000000BYPOPTHM_SmoothDer Derivative of Smoothed Unemployment level (NSA) / Population
6497 UNEMPLOYBYPOPTHM_SmoothDer Derivative of Smoothed Unemployment level, seasonally adjusted / Population
6504 NPPTTLBYPOPTHM_Smooth Savitsky-Golay Smoothed (p=3, n=365) ADP Private Employment / Population
6507 NPPTTLBYPOPTHM_Log Log of ADP Private Employment / Population
6508 NPPTTLBYPOPTHM_mva200 ADP Private Employment / Population 200 Day MA
6509 NPPTTLBYPOPTHM_mva050 ADP Private Employment / Population 50 Day MA
6510 U6toU3_YoY U6RATE minums UNRATE Year over Year
6512 U6toU3_YoY5 U6RATE minums UNRATE 5 Year over 5 Year
6515 U6toU3_SmoothDer Derivative of Smoothed U6RATE minums UNRATE
6524 CHRISCMEHG1.by.PPIACO_SmoothDer Derivative of Smoothed Copper, $/lb, Normalized by commodities producer price index
6533 CHRISCMEHG1.by.CPIAUCSL_SmoothDer Derivative of Smoothed Copper, $/lb, Normalized by consumer price index
6540 DCOILBRENTEU.by.PPIACO_Smooth Savitsky-Golay Smoothed (p=3, n=365) Crude Oil - Brent, $/bbl, Normalized by producer price index c.o.
6542 DCOILBRENTEU.by.PPIACO_SmoothDer Derivative of Smoothed Crude Oil - Brent, $/bbl, Normalized by producer price index c.o.
6544 DCOILBRENTEU.by.PPIACO_mva200 Crude Oil - Brent, $/bbl, Normalized by producer price index c.o. 200 Day MA
6545 DCOILBRENTEU.by.PPIACO_mva050 Crude Oil - Brent, $/bbl, Normalized by producer price index c.o. 50 Day MA
6549 DCOILWTICO.by.PPIACO_Smooth Savitsky-Golay Smoothed (p=3, n=365) Crude Oil - WTI, $/bbl, Normalized by producer price index c.o.
6551 DCOILWTICO.by.PPIACO_SmoothDer Derivative of Smoothed Crude Oil - WTI, $/bbl, Normalized by producer price index c.o.
6552 DCOILWTICO.by.PPIACO_Log Log of Crude Oil - WTI, $/bbl, Normalized by producer price index c.o.
6553 DCOILWTICO.by.PPIACO_mva200 Crude Oil - WTI, $/bbl, Normalized by producer price index c.o. 200 Day MA
6554 DCOILWTICO.by.PPIACO_mva050 Crude Oil - WTI, $/bbl, Normalized by producer price index c.o. 50 Day MA
6558 LBMAGOLD.USD_PM.by.PPIACO_Smooth Savitsky-Golay Smoothed (p=3, n=365) Gold, USD PM/Troy Ounce, Normalized by commodities producer price index
6560 LBMAGOLD.USD_PM.by.PPIACO_SmoothDer Derivative of Smoothed Gold, USD PM/Troy Ounce, Normalized by commodities producer price index
6563 LBMAGOLD.USD_PM.by.PPIACO_mva050 Gold, USD PM/Troy Ounce, Normalized by commodities producer price index 50 Day MA
6567 LBMAGOLD.USD_PM.by.CPIAUCSL_Smooth Savitsky-Golay Smoothed (p=3, n=365) Gold, USD/Troy OUnce, Normalized by consumer price index
6569 LBMAGOLD.USD_PM.by.CPIAUCSL_SmoothDer Derivative of Smoothed Gold, USD/Troy OUnce, Normalized by consumer price index
6572 LBMAGOLD.USD_PM.by.CPIAUCSL_mva050 Gold, USD/Troy OUnce, Normalized by consumer price index 50 Day MA
6576 LBMAGOLD.USD_PM.by.GDP_Smooth Savitsky-Golay Smoothed (p=3, n=365) Gold, USD/Troy OUnce, Normalized by GDP
6578 LBMAGOLD.USD_PM.by.GDP_SmoothDer Derivative of Smoothed Gold, USD/Troy OUnce, Normalized by GDP
6581 LBMAGOLD.USD_PM.by.GDP_mva050 Gold, USD/Troy OUnce, Normalized by GDP 50 Day MA
6585 GSG.Close.by.GDPDEF_Smooth Savitsky-Golay Smoothed (p=3, n=365) GSCI Commodity-Indexed Trust, Normalized by GDP def
6587 GSG.Close.by.GDPDEF_SmoothDer Derivative of Smoothed GSCI Commodity-Indexed Trust, Normalized by GDP def
6589 GSG.Close.by.GDPDEF_mva200 GSCI Commodity-Indexed Trust, Normalized by GDP def 200 Day MA
6590 GSG.Close.by.GDPDEF_mva050 GSCI Commodity-Indexed Trust, Normalized by GDP def 50 Day MA
6594 GSG.Close.by.GSPC.Close_Smooth Savitsky-Golay Smoothed (p=3, n=365) GSCI Commodity-Indexed Trust, Normalized by S&P 500
6596 GSG.Close.by.GSPC.Close_SmoothDer Derivative of Smoothed GSCI Commodity-Indexed Trust, Normalized by S&P 500
6598 GSG.Close.by.GSPC.Close_mva200 GSCI Commodity-Indexed Trust, Normalized by S&P 500 200 Day MA
6599 GSG.Close.by.GSPC.Close_mva050 GSCI Commodity-Indexed Trust, Normalized by S&P 500 50 Day MA
6607 GDPBYPOPTHM_mva200 GDP/Population 200 Day MA
6634 GSPC.CloseBYMDY.Close_mva200 GSPC by MDY 200 Day MA
6636 QQQ.CloseBYMDY.Close_YoY QQQ by MDY Year over Year
6648 GSPC.DailySwing_Smooth Savitsky-Golay Smoothed (p=3, n=365) S&P 500 (^GSPC) Daily Swing: (High - Low) / Open
6650 GSPC.DailySwing_SmoothDer Derivative of Smoothed S&P 500 (^GSPC) Daily Swing: (High - Low) / Open
6651 GSPC.DailySwing_Log Log of S&P 500 (^GSPC) Daily Swing: (High - Low) / Open
6652 GSPC.DailySwing_mva200 S&P 500 (^GSPC) Daily Swing: (High - Low) / Open 200 Day MA
6675 HNFSUSNSA.minus.HSN1FNSA_Smooth Savitsky-Golay Smoothed (p=3, n=365) Houses for sale - houses sold
6679 HNFSUSNSA.minus.HSN1FNSA_mva200 Houses for sale - houses sold 200 Day MA
6683 MSPUS.times.HOUST_YoY5 New privately owned units start times median price 5 Year over 5 Year
6684 MSPUS.times.HOUST_Smooth Savitsky-Golay Smoothed (p=3, n=365) New privately owned units start times median price
6686 MSPUS.times.HOUST_SmoothDer Derivative of Smoothed New privately owned units start times median price
6687 MSPUS.times.HOUST_Log Log of New privately owned units start times median price
6688 MSPUS.times.HOUST_mva200 New privately owned units start times median price 200 Day MA
6689 MSPUS.times.HOUST_mva050 New privately owned units start times median price 50 Day MA
6691 MSPUS.times.HNFSUSNSA_YoY4 New privately owned 1-family units for sale times median price 4 Year over 4 Year
6693 MSPUS.times.HNFSUSNSA_Smooth Savitsky-Golay Smoothed (p=3, n=365) New privately owned 1-family units for sale times median price
6696 MSPUS.times.HNFSUSNSA_Log Log of New privately owned 1-family units for sale times median price
6697 MSPUS.times.HNFSUSNSA_mva200 New privately owned 1-family units for sale times median price 200 Day MA
6698 MSPUS.times.HNFSUSNSA_mva050 New privately owned 1-family units for sale times median price 50 Day MA
6707 MULTPLSP500PERATIOMONTH_Mean S&P 500 TTM P/E Average (Excludes Values Greater Than 50)

Equities

Equity indexes normalized by GDP

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The last two years compare favorably with the period around the late 1950’s. Need to dig into this one.

datay <- "GSPC.Close"
ylim <- c(2000, d.GSPC.max)
my.data <- plotSimilarPeriods(df.data, dfRecession, df.symbols, datay, ylim, i.window = 60)
my.data[[1]]

Look at how the different segments of the market move

datay <- "GSPC.CloseBYMDY.Close_YoY"
ylim <- c(-50, 75)
dtStart = as.Date('1980-01-01')
plotSingle(dfRecession, df.data, "date", datay, getPlotTitle(df.symbols, datay), "Date", 
            getPlotYLabel(df.symbols, datay), c(dtStart, Sys.Date()), ylim, TRUE)

datay <- "GSPC.CloseBYMDY.Close"
ylim <- c(0, 20)
dtStart = as.Date('1980-01-01')
plotSingle(dfRecession, df.data, "date", datay, getPlotTitle(df.symbols, datay), "Date", 
            getPlotYLabel(df.symbols, datay), c(dtStart, Sys.Date()), ylim, TRUE)

S&P 500 Normalized moving average

Look at moving average relationship by dividing the S&P 500 open price by the 200 day SMA.

datay <- "GSPC.Open_mva200_Norm"
ylim <- c(50, 125)
dt.start = as.Date('2008-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dt.start)

Crossovers

Look at the 50 DMA versus 200 DMA, often used as a technical indicator of market direction.

datay <- "GSPC.Open_mva050_mva200"
ylim <- c(-200, 200)
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStartBackTest)

datay <- "GSPC.Open_mva050_mva200_sig "
ylim <- c(0.0, 1.0)
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStartBackTest)

S&P 500 TTM P/E

Take a look at some of the earnings trends from SilverBlatt’s sheet.

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Take a longer look back at as-reported and operating earnings

Market prices can out-run earnings so take a look at price to earnings.

Focus on some of the more recent activity

S&P 500 Sales

datay <- "MULTPLSP500SALESQUARTER"
ylim <- c(500, 1500)
dt.start <- as.Date('1999-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dt.start)

datay <- "MULTPLSP500SALESQUARTER"
ylim <- c(500, 1500)
dt.start = as.Date('2001-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dt.start)

Unit Profits

The series peaks in the middle of a bull market.

S&P 500 dividends

12-month real dividend per share inflation adjusted November, 2018 dollars. Data courtesy Standard & Poor’s and Robert Shiller.

https://www.quandl.com/data/MULTPL/SP500_DIV_MONTH-S-P-500-Dividend-by-Month

Evaluate year over year dividend growth.

Real value dividend growth.

datay <- "MULTPLSP500DIVMONTH_YoY"
ylim <- c(-40, 20)
dtStart = as.Date('2001-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart, b.percentile = FALSE)

S&P 500 dividend yield (12 month dividend per share)/price. Yields following September 2018 (including the current yield) are estimated based on 12 month dividends through September 2018, as reported by S&P. Sources: Standard & Poor’s for current S&P 500 Dividend Yield. Robert Shiller and his book Irrational Exuberance for historic S&P 500 Dividend Yields.

https://www.quandl.com/data/MULTPL/SP500_DIV_YIELD_MONTH-S-P-500-Dividend-Yield-by-Month

datay <- "MULTPLSP500DIVYIELDMONTH"
ylim <- c(0, 12)
dtStart = as.Date('1950-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart, b.percentile = FALSE)

datay <- "MULTPLSP500DIVYIELDMONTH"
ylim <- c(1, 4)
dtStart = as.Date('2001-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart, b.percentile = FALSE)

S&P 500 Volume

The log of the S&P volume has some interesting patterns, but nothing that seems to help with a recession indicator.

That is one spiky data series. Not sure there is a lot to help us here.

Russell 2000

Take a look at recent activity in the small cap market.

S&P 500 to Rusell 2000

Thirty day movement

Correlation

## Warning in max.default(structure(numeric(0), class = "Date"),
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S&P 500 to MDY (Mid-cap) 2000 Correlation

datay1 <- "RLG.Open"
ylim1 <- c(0, 2500)

datay2 <- "MDY.Open"
ylim2 <- c(0, 500)

dtStart <- as.Date("1jan2003","%d%b%Y")

w <- 30
corrName <-
  calcRollingCorr(dfRecession,
                  df.data,
                  df.symbols,
                  datay1,
                  ylim1,
                  datay2,
                  ylim2,
                  w,
                  dtStart)
## Warning in max.default(structure(numeric(0), class = "Date"),
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## returning -Inf
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## returning Inf

Dividend Stocks

This is an interesting series, they should perform better through the recessions. Unfortunately they are short lived so there is not much data so this is more of a place holder for now.

datay <- "NOBL.Open"
ylim <- c(40, 110)
dt.start <- as.Date('2014-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dt.start)

Margin and option data

NYSE Margin Debt

Taking a look at margin debt. NYXDATA stopped providing NYSE margin debt data on Dec 2017. Data is available from FINRA, but it includes more accounts than the data did for NYXdata. I stitched togeter the data sets: data after Jan 2010 include NYSE+Others, data prior is just NYSE account data scaled up to match the FINRA data.

It tends to creep up when there is a frenzy in the stock market.

datay <- "FINRAMarginDebt_Log"
ylim <- c(5, 15)
plotSingleQuick(dfRecession, df.data, datay, ylim)

Take a close look at recent activity

Sometimes it is more helpful to view year over year growth.

More near-term trend.

Take a look at some of the correlations

datay1 <- "FINRAMarginDebt_YoY"
ylim1 <- c(-100, 100)

datay2 <- "GSPC.Close_YoY"
ylim2 <- c(-100, 100)

dtStart <- as.Date("1jan1995","%d%b%Y")

w <- 90
corrName <-
  calcRollingCorr(dfRecession,
                  df.data,
                  df.symbols,
                  datay1,
                  ylim1,
                  datay2,
                  ylim2,
                  w,
                  dtStart)

Comparison to the Russell 2000

datay1 <- "FINRAMarginDebt_YoY"
ylim1 <- c(-100, 100)

datay2 <- "RLG.Close_YoY"
ylim2 <- c(-100, 100)

dtStart <- as.Date("1jan1995","%d%b%Y")

w <- 90
corrName <-
  calcRollingCorr(dfRecession,
                  df.data,
                  df.symbols,
                  datay1,
                  ylim1,
                  datay2,
                  ylim2,
                  w,
                  dtStart)

OCC Options Volumes

See what is happening with the options volumes for equities. (From: https://www.theocc.com/webapps/historical-volume-query)

Looks like options on non-equity co-occurs with peaks/troughs?.

Market Volatility

Take a look at some of the indications of market volatility

CBOE VIX

As markets become complacent (low VIX) and high values, peaks often occur.

Compare the VIX to some of the ETF’s out there.

There

Not much predictive in VIX, take a quick look at the smoothed derivative.

S&P Daily Swings

Daily changes in the S&P should correlate well with the VIX.

More of a correlating series than a predictor.

Employment and payrolls

Unemployment rates

Unemployment rates will probably be useful, let’s take a look at the U-3. The data is a little noisy so there is also a smoothed version plotted. There seems to be a relationship between the unemployment rate and the recessions, but it could be a lagging indicator. This will be explored a little bit more later.

Looking at the unemployment rate, the eye is drawn to the rise and fall of the data, this suggests that the derivative might be helpful as well. The figure below shows the results, using a Savitzky-Golay FIR filter. It looks like the unemployment rate peaks in the middel of the recession. That peak might be a good buy signal.

Continuing Claims

A good measure of how much unemployment is growing.

Continued claims, also referred to as insured unemployment, is the number of people who have already filed an initial claim and who have experienced a week of unemployment and then filed a continued claim to claim benefits for that week of unemployment. Continued claims data are based on the week of unemployment, not the week when the initial claim was filed

https://fred.stlouisfed.org/series/CCNSA

A good measure of how much unemployment is growing

Initial Claims

A good measure of how much unemployment is growing.

An initial claim is a claim filed by an unemployed individual after a separation from an employer. The claim requests a determination of basic eligibility for the Unemployment Insurance program.

https://fred.stlouisfed.org/series/ICSA

Unemployment rates, year-over-year

Both the headline unemployment and U-6 number changes are similar. During the upswing on the cycle it does look like the headline number falls faster than U-6

The second derivative of the unemployment rate does have zero crossings near the middle point of a recession. This would make it a helpful buy signal for the trading strategy.

Unemployment rates, similar periods

Historically the last two years of record low unemployment appear most similar to the 1971-1973 time frame. Just before inflation took off.

Unemployment rates, U-6 and headline number.

Let’s also take a look at the total unemployed, U-6. It continues to fall as the headline number stabilizes as people return to the work force. An indicator the cycle is beginning to top out.

Difference between U6 and U3 to see how close the economy is getting to full employment.

Unemployment and market bottoms

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Initial jobless claims

We will also take a look at initial jobless claims, this should start to rise just before the unemployment rate.

It looks like the jobless claim tend to peak more towards the end of the recession. It does not seem to be as strong of a sell indicator as the U-3 rate.

Jobless claims have a seasonal component to them. One way to reduce this effect is to calculate year over year growth. That helps some, the peaks seem to be more closely aligned with the middle to end of recessions.

Take a closer look at recent data

## Warning: Removed 1 rows containing missing values (geom_text).
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Take a look at the percentage of the population looking for work

A bit more recent trend

Unemployment Level

ADP data here. comes out before the official numbers.

Look at the year-over-year change in ADP.

ADP data divided by the population

Payrolls

Look at the BLS data on payrolls. Check the NSA series, then we will look at YoY data.

Hours worked

Sparked by an article at Mises (https://mises.org/wire/how-alexandria-ocasio-cortez-misunderstands-american-poverty), take a look at average weekly hours

The time series is pretty lumpy, plot the YoY change

A more recent look at average weekly hours of production

Industrial Production

Industrial production is also known to fall during an economic downturm, let’s take a look at some of the data from the FRED on industrual production. It does seem to peak prior to a recession so let’s smooth and look at the derivative as it might be a good indicator as well.

Industrial production over the last ten years or so

The derivative isn’t bad, but it sometimes crosses zeros well into a recession. That is less helpful as either a buy or sell indicator. A better measure might year over year (YoY) change.

The year over year change has a similar appearance. The low values at the beginning make the year over year values larger than the more recent values. Seems like it will rank low a reliable indicator.

datay1 <- "INDPRO_YoY"
ylim1 <- c(-20, 12)

datay2 <- "GSPC.Close_YoY"
ylim2 <- c(-100, 50)

dtStart <- as.Date("1jan1981","%d%b%Y")

w <- 360
corrName <- calcRollingCorr(dfRecession, df.data, df.symbols, datay1, ylim1, datay2, ylim2, w, dtStart)

Retail Sales

Retail sales, aggregate

Retail sales also change during recession. As the plot below shows, it seems to follow the trend of industrial production. It might be too strongly correlated to add much to the model. The will be examined in the correlation section.

The derivative of retail sales is a little more erratic than is was the industrial products. Looks like it might be helpful to include in the model as well.

Retail sales, aggregate year-over-year

Take a look at year-over-year changes

Retail sales and unemployment correlations

Let’s see how that looks on year over year basis. Interesting to compare to unemployment rates there appears to a correlation over the long term.

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There is some similarity. The rolling correlation shows the inverse relationship prior to a recession.

datay1 <- "RSALESAGG_YoY"
ylim1 <- c(-12.5, 7.5)

datay2 <- "UNEMPLOY_YoY"
ylim2 <- c(-30, 100)

dtStart <- as.Date("1jan1970","%d%b%Y")

w <- 180
corrName <- calcRollingCorr(dfRecession,df.data, df.symbols, datay1, ylim1, datay2, ylim2, w, dtStart)

Retail sales correlation and industrial production

Industrial production and retail sales look very similar so the plot below shows the 360 correlation. The corerlation does tend to fall around a recession, although 2008 was so bad that they both fell together. Not sure if it is that useful.

datay1 <- "INDPRO"
ylim1 <- c(40, 125)

datay2 <- "RSALESAGG"
ylim2 <- c(100000, 200000)

dtStart <- as.Date("1jan1981","%d%b%Y")

w <- 30
corrName <- calcRollingCorr(dfRecession, df.data, df.symbols, datay1, ylim1, datay2, ylim2, w, dtStart)

It is interesting to see the strong correlation; however, I suspect this is due to more to the shape of the trends. How do the YoY correlations look? They are a little less correlated, probably better to use in the machine learning later.

datay1 <- "INDPRO_YoY"
ylim1 <- c(-20, 20)

datay2 <- "RSALESAGG_YoY"
ylim2 <- c(-20, 20)

dtStart <- as.Date("1jan1981","%d%b%Y")

w <- 30
corrName <- calcRollingCorr(dfRecession, df.data, df.symbols, datay1, ylim1, datay2, ylim2, w, dtStart)

Advance Retail Sales

This is an advanced estimate of the retail sales value.

Also take a look at year over year

Retail sales and the labor market

Income

Real Personal Income

Real Personal Income (Excluding Transfer, Annual)

During a recession real personal income falls. In the plot the peaks can be seen prior to each recession.

datay <- "W875RX1"
ylim <- c(3000, 15000)
plotSingleQuickModern(datay, ylim)

The features we are interested in are the peaks and valleys so we’ll use the derivative to get to those. Interesting, there is usually a first zero crossing before a recession and a second during or just after the recession.

Real personal income might have some seasonal variance, but it seems the year over year change tells the same story.

Price and cost measures

This section shows price and cost measures.

Two commonly used indexes are the CPI (consumer price index) and PPI (producer price index). CPI tries to show final prices paid for goods and services by urban U.S. consumers. This index includes sales tax and imports. The PPI attempts to reflect the prices paid at all stages of production, including goods and services purchases as inputs as well as goods and services purchased by consumers from retail and producer sellers. The PPI does not include imports or sales tax. The CPI reflects all rebates and financing plans wherease the PPI reflects only those rebate and financing plans provided by the producer. For example if an automotive manufacturer offers a rebate of $500 and the dealer offers an additional rebate of $500 then the PPI would reflect only the automotive manufacturer rebate, but the CPI would reflect both rebates.

Sources; https://www.bls.gov/opub/hom/pdf/cpihom.pdf and https://www.bls.gov/opub/hom/pdf/ppi-20111028.pdf.

Consumer price index

What does CPI look like?

datay <- "CPIAUCSL"
ylim <- c(0, 300)
plotSingleQuickModern(datay, ylim)

Check out the YoY growth

datay <- "CPIAUCSL_YoY"
ylim <- c(-2, 15)
plotSingleQuickModern(datay, ylim)

CPI to PPI

Suggested by Charlie, it can be helpful to look at the relationship between producer prices and consumer prices.

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Producer Price Index (Commodities)

Commodities

Basket

Take a look at some trends of baskets of commodities.

This plot examines commodity performance relative to the GDP deflator

Crude oil

Look at a trend of West Texas Intermediate (WTI)

This is ticker data from yahoo

Take a look at both WTI and Brent crude.

Real price of crude using producer price index for commodities

Gold

As risks increase investors often flock to safe haven assets like gold. An up-tick in prices can indicate investor uncertainty. This can be seen in the nominal price plot around 1980 and again in 2007.

This plots out the real price of gold by two different deflators. PPI corrected price is a little higher, to be expected since CPI also includes the effects of sales tax and imports. The spike in 1980 is especially pronounced in this series.

See how nominal and real prices look year over year. From the long-term view seems like there is little difference in the three series. Although not shown, even over the near-term there is little difference in the series.

See how gold correlates with the VIX. Both gold and VIX should respond to investor axiety, but it doesn’t look like it correlates very well.

## `geom_smooth()` using formula 'y ~ x'
## Warning: Removed 242 rows containing non-finite values (stat_smooth).

Copper

Dr. Copper has a reputation as an indicator of economic malaise, but it does not seem to have much of a correlation with the recessions. The series below is from CME via Quandl. It has a lot of data so I am also looking at the smoothed version.

Copper is one of the commodities in the PPI so it is a bit of a proxy for how copper is doing relative to the basket of commodities.

The change in prices, year over year, do generally peak prior to a recession. The time and shape of this peak varies, but it still might be helpful. A couple of the large troughs do seem to correlate with the end of the recession. Likely this is because industrial production has also fallen.

There is some correlation between copper and the smooth recession initiator, especially at the end of the recession.

Might be easier to see correlation in a dot plot format.

## `geom_smooth()` using formula 'y ~ x'
## Warning: Removed 342 rows containing non-finite values (stat_smooth).

This is a legacy series from FRED. It has not been updated in a couple of years so I am assuming it will go away.

Oil Services

Amazing events in the first half of 2020, take a look at those

See how the players are doing

Federal Reserve

The federal reserve has an impact on the economy, here are some data series relating to that.

Little bit closer

datay <- "WALCL"
ylim <- c(0, 10000)
dtStart = as.Date('2003-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

Federal Reserve Reverse Repo Agreements

Compare liabilities to reverse repo trends

Take a look at more recent trends

Spiky, might be easier to look at year-over-year

Normalized by GDP

datay <- "WLRRAL.by.GDP"
ylim <- c(0, 4)
dtStart = as.Date('2003-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

Overnight Bank Funding Rate

“The overnight bank funding rate is calculated using federal funds transactions and certain Eurodollar transactions. The federal funds market consists of domestic unsecured borrowings in U.S. dollars by depository institutions from other depository institutions and certain other entities, primarily government-sponsored enterprises, while the Eurodollar market consists of unsecured U.S. dollar deposits held at banks or bank branches outside of the United States. U.S.-based banks can also take Eurodollar deposits domestically through international banking facilities (IBFs). The overnight bank funding rate (OBFR) is calculated as a volume-weighted median of overnight federal funds transactions and Eurodollar transactions reported in the FR 2420 Report of Selected Money Market Rates. Volume-weighted median is the rate associated with transactions at the 50th percentile of transaction volume. Specifically, the volume-weighted median rate is calculated by ordering the transactions from lowest to highest rate, taking the cumulative sum of volumes of these transactions, and identifying the rate associated with the trades at the 50th percentile of dollar volume. The published rates are the volume-weighted median transacted rate, rounded to the nearest basis point.” https://www.newyorkfed.org/markets/obfrinfo.

Secured Overnight Financing Rate

“The Secured Overnight Financing Rate (SOFR) is a broad measure of the cost of borrowing cash overnight collateralized by Treasury securities. The SOFR includes all trades in the Broad General Collateral Rate plus bilateral Treasury repurchase agreement (repo) transactions cleared through the Delivery-versus-Payment (DVP) service offered by the Fixed Income Clearing Corporation (FICC), which is filtered to remove a portion of transactions considered “specials” " https://apps.newyorkfed.org/markets/autorates/sofr

Take a look at the variation (99th - 1st percentile)

Reserve Balances with Federal Reserve Banks

Hard to get a sense of these series in the absolute. Take a look relative to GDP.

By double entry book-keeping reserves+loans (assets) = deposit (liabilities). Does that really work?

Correlation Between Reserves and Total Loans

As reserves increase there should be less lending. That correlation generally holds.

## Scale for 'y' is already present. Adding another scale for 'y', which will
## replace the existing scale.

Did the reserve balances increase after the 2016 and 2018 drops? Not in the same way. There are some relationships between the equities market and the reserves though.

Explicitly correlate reserve balances and total loans. It is a weak and noisy correlation.

## `geom_smooth()` using formula 'y ~ x'
## Warning: Removed 990 rows containing non-finite values (stat_smooth).

Interest on excess reserves

Monetary Base

Currency trend, base

This used to trend along with GDP. It doesn’t anymore.

Money supplies

Basic currency trend (currency component of M1)

datay <- "WCURRNS_YoY"
dtStart = as.Date('1980-01-01')
ylim <- c(0, 17)
myplot <- plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)
myplot

datay <- "WCURRNS_YoY"
dtStart = as.Date('2000-01-01')
ylim <- c(0, 20)
myplot <- plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)
myplot

The rate of change of money supply could be an indicator of a recession. Let’s see how that compares.

Intervention in the repo market

The federal reserve provides liquidity to the repo market, summary of that action

European central bank

The European central band (ECB) has taken a different path compared to the US Federal Reserve bank.

## Scale for 'y' is already present. Adding another scale for 'y', which will
## replace the existing scale.

Federal Debt

The government is a big driver of the economy, let’s see what it is doing in the debt markets.

datay <- "GFDEBTN"
ylim <- c(0, 35000000)
plotSingleQuick(dfRecession, df.data, datay, ylim)

datay <- "GFDEBTN_Log"
ylim <- c(12, 18)
plotSingleQuick(dfRecession, df.data, datay, ylim)

datay <- "GFDEBTN_YoY"
ylim <- c(-10, 25)
plotSingleQuick(dfRecession, df.data, datay, ylim)

Federal debt as percent GDP

datay <- "GFDEGDQ188S"
ylim <- c(30, 150)
plotSingleQuick(dfRecession, df.data, datay, ylim)

Federal deficit as percent GDP

datay <- "FYFSGDA188S"
ylim <- c(-30, 5)
plotSingleQuick(dfRecession, df.data, datay, ylim)

Charlie Hatch has a nice format of deficit versus debt:

## Scale for 'y' is already present. Adding another scale for 'y', which will
## replace the existing scale.

Nonfinancial Corporate Business Debt

What about Nonfinancial corporate business and debt securities? Hopefully this doesn’t follow the business loan trends.

That is crazy steep. Time for a log format, see if that brings out the peaks and troughs. That’s a litte better, it looks like there might be a change in slope prior to the recessions.

The derivative doesn’t seem to be much help. There is not much correlation between the zero crossings and the NEBR recessions.

Debt cycle

This analysis roughly follows the ideas in Big Debt Crises book by Ray Dalio.

Total loans

One business cycle theory describes recessions as a market adjustment to mis-allocated assets, often fueled by an credit expansion. That makes the volume of loans an interesting feature to look at. In the presentation of data it looks like the great recession had the largest impact.

Plotting the year over year growth rate helps pull out those small changes in the early years in the data. Peaks can be seen prior to most recessions.

Zoom in to the last couple of decades

As long term interest rates rise, loans should start to tick down. To check this, the total loans and 10 to 1 year spreads are plotted. This is generally the trend observed.

There is a good correlation between these two variables. This next section plots that correction explicitly.

Total loans as percent of GDP

This is the total loans. I think the picture is too broad to point to a specific sector of the economy. The debt burden assumes interest rates are tied to the 10-year treasury: (TOTLNNSA * DGS10) / 100

Commercial and industral loans

Business loans should slow before the recession (a contraction in credit as rates rise).

Commercial and industrial loans as percent of GDP and and income

Look at business debt normalized by GDP over the entire time series. This ratio often peaks at the mid-point of a recession.

https://www.wsj.com/articles/this-isnt-your-fathers-corporate-bond-market-11590574555

“Bonds are behaving more like bank debt, which tends to remain stable or even increase at the onset of recessions, as lenders keep distressed clients afloat—and only later turn off the taps. This was confirmed by a recent report from the Bank for International Settlements. It also found a tight link between this lending cycle and the “real” economy’s booms and busts."

I assume that interest is related to the 10-year treasure: (TOTCINSA * DGS10) / 100

Farm loans

See how the farming sector is fairing.

Real estate loans

Data taken from H.8 Assets and Liabilities of Commercial Banks in the United States. Take a look at SA and NSA data series as weekly and month updates. It should all be similar at this scale.

This gives a big picture, but makes it hard to connect the loans with the income needed to cover those loans. In the next section, loans will be broken up by commercial and residential.

Real Estate (Residential)

In absolute terms the mortgages have increased, but it does not appear to be out of line with the overall economy.

Normalized by GDP it is easier to see the peak in 2008 and that loan levels appear reasonable at the commercial banks.

Maybe the GSE’s are making loans. Take a look at the total mortgages from Z.1 as a percentage of GDP. That does not look too far off trend (ignoring that peak in 2008).

I am assuming that personal income is paying for the mortgages.

Real estate (residential) as percent of GDP and and income

## Warning: Removed 1 rows containing missing values (geom_text).

Consumer loans

Focusing on the consumer sector the growth in debt and incomes can be directly compared. Personal income, as a percent of GDP, remains nearly constant. It is not uncommon for the personal income to rise prior to a recession. Likely this reflect increasing asset prices and market returns. Also interesting to see the loans pick up after interest rates dropped in 1982.

Consumer loans as percent of GDP and and income

Take a closer look since the 2008 recession. Looks like loans are starting to slow as the interest burden rises and incomes remain stable. There are some anomolies in the A065RC1A027NBEA data series because it only updates onces a year. the PI series updates once a month but is noisier and seasonally adjusted. It also shows incomes rising in the middle of the 2008 recession, which doesn’t seem to be accurate.

## Warning: Removed 1 rows containing missing values (geom_text).
## Removed 1 rows containing missing values (geom_text).
## Warning: Removed 1 rows containing missing values (geom_hline).

Repo market

This market went through some stress in 2008, it is happening again so setup some plots to watch it.

Nonfincial corporate business security repo asset level

Bonds

T-Bills and Yield Curve

Speaking of loans, interest rates also play into this. This analysis will focus on treasure bills. The 3-month is plotted below. The yield flattens before a recession as investors go long on bonds and short on equities.

datay <- "TB3MS"
datay.aux <- "DTB3"
ylim <- c(0, 20)
p1 <- plotSingleQuickModern(datay, ylim)
p1 + geom_line(data=df.data, aes_string(x="date", y=datay.aux, colour=shQuote(datay.aux)), na.rm = TRUE)

datay <- "TB3MS"
datay.aux <- "DTB3"
ylim <- c(0, 2.5)
dtStart = as.Date('2017-01-01')
p1 <- plotSingle(dfRecession, df.data, "date", datay, getPlotTitle(df.symbols, datay), "Date", 
            getPlotYLabel(df.symbols, datay), c(dtStart, Sys.Date()), ylim, TRUE)
p1 + geom_line(data=df.data, aes_string(x="date", y=datay.aux, colour=shQuote(datay.aux)), na.rm = TRUE)

# {r bond3monthlibor, echo=FALSE } # # datay <- "TB3MS" # datay_aux <- "USD1MTD156N" # ylim <- c(0, 12) # dtStart = as.Date('1985-01-01') # myPlot <- plotSingle(dfRecession, df.data, "date", datay, getPlotTitle(df.symbols, datay), "Date", # getPlotYLabel(df.symbols, datay), c(dtStart, Sys.Date()), ylim, TRUE) # myPlot <- myPlot + geom_line(data=df.data, aes_string(x="date", y=datay_aux, colour=shQuote(datay_aux)), na.rm = TRUE) # # myPlot # # Check out LIBOR and fed funds rate

The 1-year is plotted below. The yield flattens before a recession as investors go long on bonds and short on equities.

datay <- "DGS10"
datay.aux <- "TNX.Close"
ylim <- c(0, 20)
p1 <- plotSingleQuickModern(datay, ylim)
p1 + geom_line(data=df.data, aes_string(x="date", y=datay.aux, colour=shQuote(datay.aux)), na.rm = TRUE)

Close in, the trend towards inversion be more easily seen. I am also comparing data from the CBOE as well as FRED.

Bond yields are a good proxy for interest rates. As rates rise the theory goes that loans should decrease (inverse correlation).

And a longer window

The yield curve (30 year bond rate minus the 10 year bond rate) may not be a good recession indicator, but a collapse is not good (https://blogs.wsj.com/moneybeat/2018/04/30/theres-more-than-one-part-of-the-yield-curve-getting-flatter/).

The yield curve (10 year bond rate minus the 1 year bond rate) seems to a good indicator of an oncoming recession. It could be a buy indicator by itself.

More recent data

Just the last 24 months or so.

Plot the 10 Year to 3 month over a few decades to see what the outling cases look like

The last two year compare favorably with the period around the 2015-2016 turndown, driven primarily by slowing of the Chinese GDP. Not a debt-driven cycle.

This plot format was suggested by a mises.org article (https://mises.org/wire/yield-curve-accordion-theory), but they only went back to 1988. The date seemed arbitrary so I went back further in time.

Take a look at more recent data

Try looking at a 1-year average of the above time series

High quality bonds

datay <- "AAA"
ylim <- c(1.5, 10)
dtStart = as.Date('1997-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

High quality bonds to 10-year treasury

High quality bonds long-term trend.

datay <- "DGS10ByAAA"
ylim <- c(1, 6.0)
dtStart = as.Date('1967-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

High quality bonds near-term trend.

datay <- "DGS10ByAAA"
ylim <- c(1, 6.0)
dtStart = as.Date('2007-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

High yield spread

“This data represents the Option-Adjusted Spread (OAS) of the ICE BofAML US Corporate A Index, a subset of the ICE BofAML US Corporate Master Index tracking the performance of US dollar denominated investment grade rated corporate debt publicly issued in the US domestic market. This subset includes all securities with a given investment grade rating A. The ICE BofAML OASs are the calculated spreads between a computed OAS index of all bonds in a given rating category and a spot Treasury curve. An OAS index is constructed using each constituent bond‚Äôs OAS, weighted by market capitalization. When the last calendar day of the month takes place on the weekend, weekend observations will occur as a result of month ending accrued interest adjustments.”

  • ICE Benchmark Administration Limited (IBA), ICE BofAML US Corporate A Option-Adjusted Spread [BAMLC0A3CA], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/BAMLC0A3CA, July 4, 2019.
datay <- "BAMLC0A3CA"
ylim <- c(0, 7)
dtStart = as.Date('1997-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

Municipal bond market

Suggest by a WSJ article, change in volume for high-risk muni’s. Doesn’t look like there is much too it yet.

https://www.wsj.com/articles/risky-municipal-bonds-are-on-a-hot-streak-11558949401?mod=hp_lead_pos3

datay <- "HYMB.Close"
ylim <- c(40, 62)
dtStart = as.Date('2011-01-01')
p1 <- plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

p1 <-
  p1 + geom_vline(
    xintercept = as.Date("2015-08-24"),
    linetype = "dashed",
    color = "grey",
    size = 1.0
  )

p1 <-
  p1 + geom_vline(
    xintercept = as.Date("2016-01-08"),
    linetype = "dashed",
    color = "grey",
    size = 1.0
  )
p1 <-
  p1 + geom_vline(
    xintercept = as.Date("2018-02-05"),
    linetype = "dashed",
    color = "grey",
    size = 1.0
  )
p1 <-
  p1 + geom_vline(
    xintercept = as.Date("2018-10-11"),
    linetype = "dashed",
    color = "grey",
    size = 1.0
  )

datay <- "HYMB.Volume"
ylim <- c(0, 1750000)
p1.vol <- plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

p1.vol <-
  p1.vol + geom_vline(
    xintercept = as.Date("2015-08-24"),
    linetype = "dashed",
    color = "grey",
    size = 1.0
  )

p1.vol <-
  p1.vol + geom_vline(
    xintercept = as.Date("2016-01-08"),
    linetype = "dashed",
    color = "grey",
    size = 1.0
  )
p1.vol <-
  p1.vol + geom_vline(
    xintercept = as.Date("2018-02-05"),
    linetype = "dashed",
    color = "grey",
    size = 1.0
  )
p1.vol <-
  p1.vol + geom_vline(
    xintercept = as.Date("2018-10-11"),
    linetype = "dashed",
    color = "grey",
    size = 1.0
  )


datay <- "GSPC.Open"
datay_aux <- "GSPC.Close"
ylim <- c(1500, d.GSPC.max )
p2 <-
  plotSingle(
    dfRecession,
    df.data,
    "date",
    datay,
    getPlotTitle(df.symbols, datay),
    "Date",
    getPlotYLabel(df.symbols, datay),
    c(dtStart, Sys.Date()),
    ylim,
    TRUE
  )

p2 <-
  p2 + geom_vline(
    xintercept = as.Date("2015-08-24"),
    linetype = "dashed",
    color = "grey",
    size = 1.0
  )
p2 <-
  p2 + geom_vline(
    xintercept = as.Date("2016-01-08"),
    linetype = "dashed",
    color = "grey",
    size = 1.0
  )
p2 <-
  p2 + geom_vline(
    xintercept = as.Date("2018-02-05"),
    linetype = "dashed",
    color = "grey",
    size = 1.0
  )
p2 <-
  p2 + geom_vline(
    xintercept = as.Date("2018-10-11"),
    linetype = "dashed",
    color = "grey",
    size = 1.0
  )


grid.arrange(p1,
             p1.vol,
             p2,
             ncol = 1,
             top = "High Yield Muni's and S&P Price")

Total Loans and yield curve correlation

This relationship was suggest by Charlie and it is an interesting one. As the yield curve flattens (10-year and 1-year rates converge), total loans grow. The generalization is not always accurate, but it does fit.

## `geom_smooth()` using formula 'y ~ x'

I wanted to see how this looked compared to the 3 month

## `geom_smooth()` using formula 'y ~ x'
## Warning: Removed 282 rows containing non-finite values (stat_smooth).

Consumer loans and yield curve correlation

Compared to business loans, consumer loans seem to have to response to the 10Y to 3M yield curve.

## `geom_smooth()` using formula 'y ~ x'
## Warning: Removed 311 rows containing non-finite values (stat_smooth).

Business loans and yield curve correlation

## `geom_smooth()` using formula 'y ~ x'
## Warning: Removed 105 rows containing non-finite values (stat_smooth).

That’s pretty good correlation. Let’s see what the rolling correlation looks like.

datay1 <- "TOTLNNSA_YoY"
ylim1 <- c(-10, 20)

datay2 <- "DGS10TO1"
ylim2 <- c(-5, 10)

dtStart <- as.Date("1jan1960","%d%b%Y")

w <- 360
corrName <- calcRollingCorr(dfRecession, df.data, df.symbols, datay1, ylim1, datay2, ylim2, w, dtStart)

datay1 <- "TOTLNNSA_YoY"
ylim1 <- c(-10, 20)

datay2 <- "DGS10TO1"
ylim2 <- c(-5, 10)

dtStart <- as.Date("1jan1960","%d%b%Y")

w <- 720
corrName <- calcRollingCorr(dfRecession, df.data, df.symbols, datay1, ylim1, datay2, ylim2, w, dtStart)

One other items, let’s see how loans do versus the federal funds rate

## `geom_smooth()` using formula 'y ~ x'

Baker Hughes Rig Count

BEA Supplemental Estimates, Motor Vehicles

Definitions

Autos–all passenger cars, including station wagons.
Light trucks–trucks up to 14,000 pounds gross vehicle weight, including minivans and
sport utility vehicles. Prior to the 2003 Benchmark Revision light trucks were up to 10,000 pounds.
Heavy trucks–trucks more than 14,000 pounds gross vehicle weight.
Prior to the 2003 Benchmark Revision heavy trucks were more than 10,000 pounds.
Domestic sales–United States (U.S.) sales of vehicles assembled in the U.S., Canada, and Mexico.
Foreign sales–U.S. sales of vehicles produced elsewhere.
Domestic auto production–Autos assembled in the U.S.
Domestic auto inventories–U.S. inventories of vehicles assembled in the U.S., Canada, and Mexico.

TAble 6 - Light Vehicle and Total Vehicle Sales

Auto sales

A WSJ article suggested that auto sales might be a good indicator so bring that to the mix. It does have troughs that correlate with recessions

There might be some seasonal variance in the auto sales so lets take a look at the year over year. The data is pretty noisy, it probably will not make a very good indicator.

BEA Gross Domestic Product

Data in this section come from the Bureau of Economic Analysis.

Table 1.1.5. Gross Domestic Product

[Billions of dollars] Seasonally adjusted at annual rates

A191RC: Gross Domestic Product - Line 1

GDP numbers tend to lag so this series is truly an afterthought. But it does have some correlation with the recessions.

GDP does not reflect the capacity of the economy nor the efficiency. Shrinking capacity and lower prices at constant volumes would indicate improvements in effeciency/productivity which is good for the economy, but does not move the GDP upward.

Looks like the year over year change on the GDP should correlate well with unemployment.

Table 1.1.9. Implicit Price Deflators for Gross Domestic Product

[Index numbers, 2012=100] Seasonally adjusted

A191RD: Gross Domestic Product - Line 1

This is GDP price deflator series.

GDP normalized by CPI

Normalize GDP by CPI

Economic yield curve (GDP to 1-year treasury)

GDP versus the yield on the 1-year. This series was prompted by an article suggesting that the “economic yield curve” should be used to indicate a recession rather than an inverted yield curve. Less of indicator and more of concurrent confirmation of recession. Not sure why they would be related either.

Economic yield curve (GDP to 3-month treasury)

Same idea as above, but applied the 3-month treasury.This one has fewer false triggers, but is not as helpful as 10Y to 3M spread in predicting a recession.

A824RC: National defense Federal Gov’t Expenditures - Line 24

U.S. Bureau of Economic Analysis, Federal Government: National Defense Consumption Expenditures and Gross Investment [FDEFX], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/FDEFX, April 6, 2021.

A825RC: Nondefense Federal Gov’t Expenditures - Line 25

U.S. Bureau of Economic Analysis, Federal Government: Nondefense Consumption Expenditures and Gross Investment [FNDEFX], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/FNDEFX, April 6, 2021.

Table 6.16D. Corporate Profits by Industry

Select series from Table 6.16D

A051RC: Corporate profits with inventory and capital consumption adjustment

From BEA’s documentation (https://www.bea.gov/media/5671):

“BEA’s featured measure of corporate profits — profits from current production - provides a comprehensive and consistent economic measure of the income earned by all U.S. corporations. As such, it is unaffected by changes in tax laws, and it is adjusted for nonreported and misreported income. It excludes dividend income, capital gains and losses, and other financial flows and adjustments, such as deduction for “bad debt.” Thus, the NIPA measure of profits is a particularly useful analytical measure of the health of the corporate sector. For example, in contrast to other popular measures of corporate profits, the NIPA measure did not show the large run-up in profits during the late 1990s that was primarily attributable to capital gains.

Profits after tax with IVA and CCAdj is equal to corporate profits with IVA and CCAdj less taxes on corporate income. It provides an after-tax measure of profits from current production."

Data is Line 1 of Table 6.16D

A053RC: Corporate profits without inventory and capital consumption adjustment

Profits look a bit flat over the last several years in this series.

Table 2.6. Personal Income and Its Disposition, Monthly

Billions of dollars; months are seasonally adjusted at annual rates.

A065RC Personal Income - Line 1

BEA Account Code: A065RC

Personal income is the income that persons receive in return for their provision of labor, land, and capital used in current production and the net current transfer payments that they receive from business and from government.25 Personal income is equal to national income minus corporate profits with inventory valuation and capital consumption adjustments, taxes on production and imports less subsidies, contributions for government social insurance, net interest and miscellaneous payments on assets, business current transfer payments (net), current surplus of government enterprises, and wage accruals less disbursements, plus personal income receipts on assets and personal current transfer receipts. A Guide to the National Income and Product Accounts of the United States (NIPA) - (http://www.bea.gov/national/pdf/nipaguid.pdf)

Suggested Citation: U.S. Bureau of Economic Analysis, Personal Income [PI], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/PI, July 11, 2019.

DPCERC: Personal consumption expenditures (PCE) - Table 2.1, Line 29

BEA Account Code: DPCERC Personal consumption expenditures (PCE) is the primary measure of consumer spending on goods and services in the U.S. economy. 1 It accounts for about two-thirds of domestic final spending, and thus it is the primary engine that drives future economic growth. PCE shows how much of the income earned by households is being spent on current consumption as opposed to how much is being saved for future consumption. -https://www.bea.gov/system/files/2019-12/Chapter-5.pdf

Suggested Citation: U.S. Bureau of Economic Analysis, Personal Consumption Expenditures [PCE], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/PCE, June 12, 2020

DPCERG: Personal consumption expenditures Price Index (PCEPI) - Table 2.1, Line 29

BEA Account Code: DPCERG The gross domestic product price index measures changes in prices paid for goods and services produced in the United States, including those exported to other countries. Prices of imports are excluded. The gross domestic product implicit price deflator, or GDP deflator, basically measures the same things and closely mirrors the GDP price index, although the two price measures are calculated differently. The GDP deflator is used by some firms to adjust payments in contracts.

The gross domestic purchases price index is BEA’s featured measure of inflation for the U.S. economy overall. It measures changes in prices paid by consumers, businesses, and governments in the United States, including the prices of the imports they buy.

BEA’s closely followed personal consumption expenditures price index, or PCE price index, is a narrower measure. It looks at the changing prices of goods and services purchased by consumers in the United States. It’s similar to the Bureau of Labor Statistics’ consumer price index for urban consumers. The two indexes, which have their own purposes and uses, are constructed differently, resulting in different inflation rates.

The PCE price index is known for capturing inflation (or deflation) across a wide range of consumer expenses and for reflecting changes in consumer behavior. For example, if the price of beef rises, shoppers may buy less beef and more chicken. Also, BEA revises previously published PCE data to reflect updated information or new methodology, providing consistency across decades of data that’s valuable for researchers. The PCE price index is used primarily for macroeconomic analysis and forecasting. -https://www.bea.gov/resources/learning-center/what-to-know-prices-inflation

Suggested Citation: U.S. Bureau of Economic Analysis, Personal Consumption Expenditures: Chain-type Price Index [PCEPI], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/PCEPI, April 25, 2021.

A072RC: Personal Savings Rate - Line 35

Consumers tend to pull down their savings rates as unemployment decreases and market conditions improve. This series has tended to be unreliable due to the size of revisions during the comprehensive update carried out by the BEA. The last update on this series moved the rate from 4.2 to 6.7 percent.

(https://www.bloomberg.com/news/articles/2018-07-27/americans-have-been-saving-much-more-than-thought-new-data-show)

BEA Account Code: A072RC Personal saving as a percentage of disposable personal income (DPI), frequently referred to as “the personal saving rate,” is calculated as the ratio of personal saving to DPI. Personal saving is equal to personal income less personal outlays and personal taxes; it may generally be viewed as the portion of personal income that is used either to provide funds to capital markets or to invest in real assets such as residences.(https://www.bea.gov/national/pdf/all-chapters.pdf) A Guide to the National Income and Product Accounts of the United States (NIPA).

Suggested Citation: U.S. Bureau of Economic Analysis, Personal Saving Rate [PSAVERT], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/PSAVERT, July 9, 2019.

Take a closer look at the last decade

The relationship between personal savings and unemployment (U-3) can be better visualized with a scatter plot

## `geom_smooth()` using formula 'y ~ x'
## Warning: Removed 190 rows containing non-finite values (stat_smooth).

The fit does not explain most of what is in the plot. Lets take a look at the rolling correlation.

datay1 <- "UNRATE"
ylim1 <- c(2, 12)

datay2 <- "PSAVERT"
ylim2 <- c(0, 35)

dtStart <- as.Date("1jan1985","%d%b%Y")

w <- 360
corrName <- calcRollingCorr(dfRecession, df.data, df.symbols, datay1, ylim1, datay2, ylim2, w, dtStart)

Personal savings to household net worth

A relationship between personal savings and household networth can be seen in a scatter plot. This was suggested by a WSJ article (https://blogs.wsj.com/dailyshot/2018/02/23/the-daily-shot-reasons-for-declining-u-s-household-savings-rate/).

## `geom_smooth()` using formula 'y ~ x'
## Warning: Removed 589 rows containing non-finite values (stat_smooth).

U.S. Census Bureau

U.S. International Trade in Goods and Services (FT900)

U.S. Bureau of Economic Analysis and U.S. Census Bureau, U.S. Imports of Goods by Customs Basis from China [IMPCH], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/IMPCH, October 5, 2019.

New Houses Sold and For Sale by Stage of Construction and Median Number of Months on Sales Market

Read an article suggesting that housing sales and sales growth could be useful. FRED only has new home data so start there.

datay <- "HSN1FNSA"
ylim <- c(0, 200)
dtStart = as.Date('1964-01-01')
p1 <- plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

datay <- "HNFSUSNSA"
ylim <- c(0, 600)
p2 <- plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

datay <- "HNFSUSNSA.minus.HSN1FNSA"
ylim <- c(0, 600)
p3 <-
  plotSingle(
    dfRecession,
    df.data,
    "date",
    datay,
    getPlotTitle(df.symbols, datay),
    "Date",
    getPlotYLabel(df.symbols, datay),
    c(dtStart, Sys.Date()),
    ylim,
    TRUE
  )

grid.arrange(p1,
             p2,
             p3,
             ncol = 1,
             top = "New Housing Sales")

New housing yoy

New Privately-Owned Housing Units Authorized in Permit-Issuing Places

As provided by the Census, start occurs when excavation begins for the footings or foundation of a building. All housing units in a multifamily building are defined as being started when this excavation begins. Beginning with data for September 1992, estimates of housing starts include units in structures being totally rebuilt on an existing foundation.

Suggested Citation: U.S. Census Bureau and U.S. Department of Housing and Urban Development, Housing Starts: Total: New Privately Owned Housing Units Started [HOUST], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/HOUST, June 13, 2020.

Take a look at privately owned starts

New Privately-Owned Houses Sold and For Sale

Suggested Citation: U.S. Census Bureau and U.S. Department of Housing and Urban Development, Median Sales Price of Houses Sold for the United States [MSPUS], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/MSPUS, June 13, 2020.

Finally, take a look at starts times the median price

Durable Goods

Suggested Citation: U.S. Census Bureau, Manufacturers’ New Orders: Durable Goods [UMDMNO], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/UMDMNO, April 26, 2021.

Durable goods, not seasonally adjusted, divided by GDP

Durable goods, seasonally adjusted, divided by GDP

Federal reserve board H.8: Assets and Liabilities of Commercial Banks in the United States

Page 4: Not Seasonally adjusted, billions of dollars

Commercial and industrial loans, all commercial banks - Line 10

Data taken from H.8 Assets and Liabilities of Commercial Banks in the United States. Take a look at SA and NSA data series as weekly and month updates. It should all be similar at this scale.

Suggested Citation: Board of Governors of the Federal Reserve System (US), Commercial and Industrial Loans, All Commercial Banks [BUSLOANS], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/BUSLOANS, July 11, 2019.

Taking a look at the difference in SA and NSA series. Seasonal adjustments do vary, but do not seem to be related to recessions.

The raw series is just too steep for any kind of machine learnine. This needs to be converted to log scale.

That’s a little better, let’s see what the smoothed derivative looks like.

That is odd…looks like this doesn’t cross zero unless we are getting close to, or into, a recession. The year over year tells about the same story. Might be a good indication of the end of a recession.

Consumer loans, all commercial banks - Line 20

Suggested Citation: Board of Governors of the Federal Reserve System (US), Consumer Loans, All Commercial Banks [CONSUMERNSA], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/CONSUMERNSA, July 11, 2019.

That spike in consumer loans is due to

“April 9, 2010 (Last revised September 23, 2011): As of the week ending March 31, 2010, domestically chartered banks and foreign-related institutions had consolidated onto their balance sheets the following assets and liabilities of off-balance-sheet vehicles, owing to the adoption of FASB’s Financial Accounting Statements No. 166 (FAS 166),”Accounting for Transfers of Financial Assets," and No. 167 (FAS 167), “Amendments to FASB Interpretation No. 46(R).”

This included a consumer loans, credit cards and other revolving plans change of $321.9B. That was a lot of off-balance-sheet bank assets.

Deposits, All Commercial Banks, all commercial banks - Line 34

Data taken from H.8 Assets and Liabilities of Commercial Banks in the United States. Take a look at SA and NSA data series as weekly and month updates. It should all be similar at this scale.

Suggested Citation: Board of Governors of the Federal Reserve System (US), Deposits, All Commercial Banks [DPSACBW027SBOG], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/DPSACBW027SBOG, May 14, 2020.

Federal reserve board Z.1: Financial Accounts of the United States

From the FRED website (https://fred.stlouisfed.org/release?rid=52):

"The Financial Accounts (formerly known as the Flow of Funds accounts) are a set of financial accounts used to track the sources and uses of funds by sector. They are a component of a system of macroeconomic accounts including the National Income and Product accounts (NIPA) and balance of payments accounts, all of which serve as a comprehensive set of information on the economy’s performance.(1) Some important inferences that can be drawn from the Financial accounts are the financial strength of a given sector, new economic trends, changes in the composition of wealth, and development of new financial instruments over time.(1)

Sectors are compiled into three categories: households, nonfinancial businesses, and banks. The sources of funds for a sector are its internal funds (savings from income after consumption) and external funds (loans from banks and other financial intermediaries). (1) Funds for a given sector are used for its investments in physical and financial assets. Dividing sources and uses of funds into two categories helps the staff of the Federal Reserve System pay particular attention to external sources of funds and financial uses of funds.(2) One example is whether households are borrowing more from banks—or in other words, whether household debt is rising. Another example might be whether banks are using more of their funds to provide loans to consumers. Transactions within a sector are not shown in the accounts; however, transactions between sectors are.(2) Monitoring the external flows of funds provides insights into a sector’s health and the performance of the economy as a whole.

Data for the Financial accounts are compiled from a large number of reports and publications, including regulatory reports such as those submitted by banks, tax filings, and surveys conducted by the Federal Reserve System.(2) The Financial accounts are published quarterly as a set of tables in the Federal Reserve’s Z.1 statistical release.

  1. Teplin, Albert M. “The U.S. Flow of Funds Accounts and Their Uses.” Federal Reserve Bulletin, July 2001; http://www.federalreserve.gov/pubs/bulletin/2001/0701lead.pdf.
  2. Board of Governors of the Federal Reserve System. “Guide to the Flow of Funds Accounts.” 2000, http://www.federalreserve.gov/apps/fof/."

L.102 Nonfinancial Business

FL102051003.Q: Nonfinancial corporate business; security repurchase agreements; asset

Asset level of nonfinancial business security repo agreements. federalreserve.gov/apps/fof/SeriesAnalyzer.aspx?s=FL102051003&t=

L.214 Loans

FL894123005.Q: All sectors; total loans; liability

Sum of domestic financial sectors, all sectors, total mortgages, and households/non-profits. federalreserve.gov/apps/fof/SeriesAnalyzer.aspx?s=FL894123005&t=L.107&bc=L.107:FL793068005&suf=Q

FL793068005.Q: Domestic financial sectors; depository institution loans n.e.c.; asset

Sum of Monetary authority; depository institution loans n.e.c.; asset and Private depository institutions; depository institution loans n.e.c.; asset. federalreserve.gov/apps/fof/SeriesAnalyzer.aspx?s=FL793068005&t=L.214&suf=Q

FL893169005.Q: All sectors; other loans and advances; liability

Sum of finance, government, and chartered institutions asset levels. https://www.federalreserve.gov/apps/fof/SeriesAnalyzer.aspx?s=FL893169005&t=L.214&suf=Q

FL893065105.Q: All sectors; home mortgages; asset

https://www.federalreserve.gov/apps/fof/DisplayTable.aspx?t=L.214

FL893065405.Q: All sectors; multifamily residential mortgages; asset

https://www.federalreserve.gov/apps/fof/SeriesAnalyzer.aspx?s=FL893065405&t=L.214&suf=Q

FL893065505.Q: All sectors; commercial mortgages; asset

https://www.federalreserve.gov/apps/fof/SeriesAnalyzer.aspx?s=FL893065505&t=L.214&suf=Q

FL153166000.Q: Households and nonprofit organizations; consumer credit; liability

federalreserve.gov/apps/fof/SeriesAnalyzer.aspx?s=FL153166000&t=L.214&suf=Q

B.101 Balance Sheet of Households and Nonprofit Organizations

FL152000005.Q: Households and nonprofit organizations; total assets, Level

string.source ID: FL152000005.Q.

FL152090006.Q: Household Net Worth as Percentage of Disposable Personal Income

string.source ID: FL152090006.Q. Household networth tends to fall as a recession start.

Productivity Yield Curve

GDP versus productivity

Manufacturing output and employees

Not sure if these relates to a recession, but fascinating to see how output and employees change with time.

datay <- "OUTMS"
ylim <- c(60, 120)
dtStart = as.Date('1987-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

datay <- "MANEMP"
ylim <- c(10000, 20000)
dtStart = as.Date('1948-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

datay <- "PRS30006163"
ylim <- c(40, 120)
dtStart = as.Date('1986-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

Shipping volumes might be helpful in determining state of the economy.

datay <- "FRGSHPUSM649NCIS"
ylim <- c(0.8, 1.4)
dtStart = as.Date('1999-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

datay <- "FRGSHPUSM649NCIS_YoY"
ylim <- c(-30, 30)
dtStart = as.Date('1999-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

Freight, loosely, moves inversely to the trade deficit.

datay <- "BOPGTB_YoY"
ylim <- c(-30, 30)
dtStart = as.Date('1999-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

World bank air transportation. Only updated annually so less usefull, but interesting reference to above.

datay <- "WWDIWLDISAIRGOODMTK1"
ylim <- c(0, 250000)
dtStart = as.Date('1999-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

Gross private domestic investment

Spending most certainly tips down prior to a recession. The gross private domestic investment data series, plotted in log format below, show how private investment pulls back prior to recessions.

The change in direction is a little easier to see if the derivative is plotted, first YoY then the smoothed derivative

Velocity

Productivity

Date range to match census data

PMI

Industrial Production

This is a look at manufacturing industrial production. The yoY change should be a leading indicator of unemployment.

Housing

Take a look at housing starts. These can drop as rates rise.

Case-schiller price index

Population data

Many of the economic series can be better understood if normalized by population. Basic population and worker data from FRED.

Population to GDP

Look at GDP divided by CPI per person. It flattens and even dips a little prior to a recession. Might be worth looking at the derivative of this series.

That is worth a closer look

datay1 <- "GDPBYCPIAUCSLBYPOPTHM_SmoothDer"
ylim1 <- c(-5, 5)

datay2 <- "RecInit_Smooth"
ylim2 <- c(0, 1)

dtStart <- as.Date("1jan1960","%d%b%Y")

w <- 30
corrName <- calcRollingCorr(dfRecession, df.data, df.symbols, datay1, ylim1, datay2, ylim2, w, dtStart)

Correlation Study

Detailed correlations are explored above. Before concluding, let’s take a look at some overall correlation values to see if anything pops out.

Commodities

As mentioned above, copper, year over year, has some correlation with the recession initiation. It could be useful.

GDP Series

GDP, normalized first by CPI and then by population, looks like it migh correlate inversely with the recession indicators

Financials

Let’s see where we are so far. The correlation plot confirms some of the speculation above. The S&P 500 (GSPC.Open) is well correlated with industrial production (INDPRO), business loans (BUSLOANS), total loans (TOTLNNSA) , and nonfinancial corporate business debt (NCBDBIQ027S).

In this case, I want and indicator that rises prior to a recession. It looks like the unemployment rate (UNRATE), real personal income (W875RX1), and the yield curve (DGS10TO1) are all inversely correlated with the recession initiation indicator.

I thought the modified recession initiation would be a harder match, but there are quite a few correlated variables. Lets take a look at some of those in more detail

Complete list of symbols

Since it is tedious to do this one at a time, all the symbols were entered into a data frame, loaded, and aggregated together in a single xts object.

This is the complete list of symbol names and sources used in the project.